While the choice of matrix versus item-by-item questions has received considerable attention in the literature, it is still unclear in what situation one is better than the other. Building upon the previous findings, this study expands this line of research by examining whether the difference between the two question types is moderated by the number of response options. Through a web survey experiment, this study compares matrix and item-by-item questions with 2, 3, 4, 5, 7, 9, and 11 response options. Additionally, we also investigate the impact of the device used to complete the survey on data quality. The results show that straight lining and response time are similar between the two question types across all response lengths, but item nonresponse tends to be higher for matrix than item-by-item question, especially among mobile respondents. Also measurement models reveal measurement equivalence between the two question types when there are fewer than seven response options. For matrices with 9 or 11 response options, analyses reveal substantial differences compared to item-by-item questions.
Hundreds of papers have been published using Twitter data, but few previous papers report the digital divide among Twitter users. British Twitter users are younger, wealthier, and better educated than other Internet users, who in turn are younger, wealthier, and better educated than the off-line British population. American Twitter users are also younger and wealthier than the rest of the population, but they are not better educated. Twitter users are disproportionately members of elites in both countries. Twitter users also differ from other groups in their online activities and their attitudes. These biases and differences have important implications for research based on Twitter data. The unrepresentative characteristics of Twitter users suggest that Twitter data are not suitable for research where representativeness is important, such as forecasting elections or gaining insight into attitudes, sentiments, or activities of large populations. In general, Twitter data seem to be more suitable for corporate use than for social science research.
Due to a rising mobile device penetration, Web surveys are increasingly accessed and completed on smartphones or tablets instead of desktop computers or laptops. Mobile Web surveys are also gaining popularity as an alternative self-administered data collection mode among survey researchers. We conducted a methodological experiment among iPhone owners and compared the participation and response behavior of three groups of respondents: iPhone owners who started and completed our survey on a desktop or laptop PC, iPhone owners who self-selected to complete the survey on an iPhone, and iPhone owners who started on a PC but were requested to switch to iPhone. We found that respondents who completed the survey on a PC were more likely to be male, to have a lower educational level, and to have more experience with Web surveys than mobile Web respondents, regardless of whether they used the iPhone voluntarily or were asked to switch from a PC to an iPhone. Overall, iPhone respondents had more missing data and took longer to complete the survey than respondents who answered the questions on a PC, but they also showed less straightlining behavior. There are only minimal device differences on survey answers obtained from PCs and iPhones.
Web surveys permit researchers to use graphic or symbolic elements alongside the text of response options to help respondents process the categories. Smiley faces are one example used to communicate positive and negative domains. How respondents visually process these smiley faces, including whether they detract from the question’s text, is understudied. We report the results of two eye-tracking experiments in which satisfaction questions were asked with and without smiley faces. Respondents to the questions with smiley faces spent less time reading the question stem and response option text than respondents to the questions without smiley faces, but the response distributions did not differ by version. We also find support that lower literacy respondents rely more on the smiley faces than higher literacy respondents.
Twitter is one of the most popular online social network platforms for political communication. This study explains how political candidates in five countries increase their online popularity and visibility by their behavior on Twitter. Also, the study focuses on cultural differences in online social relations by comparing political candidates in five countries in the East and West: South Korea, Japan, United Kingdom, Canada, and the Netherlands. Findings show that signing up to Twitter as early as possible increases one’s online popularity as predicted by the process of preferential attachment. Candidates actively following citizens and sending undirected tweets also increases the group of followers. This doesn’t apply however to conversational tweets, which decreases the number of a candidate’s followers slightly. South Korea, having a collectivistic culture, shows higher levels of reciprocity on Twitter, although this does not increase the group of followers. In other countries, including collectivistic Japan, candidates reciprocate less frequently with citizens, effectively using Twitter more as a mass medium for broadcasting.
Web surveys technically allow providing feedback to the respondents based on their previous responses. This personalized feedback may increase respondents’ motivation and possibly the accuracy of responses. While past studies mainly concentrate on the effects of providing study results on future response rates, thus far survey research lacks theoretical and empirical contributions on the effects of personalized, immediate, feedback on response behavior. To test this, we implemented a randomized trial in the context of the Berlin Aging Study II (BASE-II) in 2014, providing feedback regarding the respondents’ personality tests (Big Five Personality Inventory) to a subgroup of the sample. Results show only moderate differences in response behavior between experimental and control groups. However, we find that respondents who received personalized feedback report higher levels of satisfaction with the survey.
In today’s fast changing world, the Internet plays a major role in people’s lives. Apart from its benefits, the Internet also has serious negative consequences which include the issue of Internet addiction. This study explores the role of demographics (e.g., age, gender, and occupational position) in relation to Internet addiction. In addition, the influence of individual psychological variables (loneliness, shyness, and proactive personality) on Internet addiction was also examined.
A structured questionnaire consisting of items representing loneliness, shyness, proactiveness, Internet addiction, and demographics was used to collect the data from 1,000 working adults in selected organizations. Chi-square tests were used to investigate the effect of gender, age, and occupational positions on Internet addiction. The influence of variables such as loneliness, shyness, and proactiveness on Internet addiction was analyzed using partial least squares structural equation modeling (PLS-SEM).
The results demonstrated no significant differences in terms of Internet addiction between the genders. However, significant differences were found in Internet addiction depending on age and occupational positions. The study also found positive relationship between loneliness, shyness, proactiveness, and Internet addiction.
The findings of this study add empirical evidence to the existing literature in respect of the correlation between age, gender, occupational position, psychological characteristics (loneliness, shyness, and proactiveness), and Internet addiction.
Sampling of migrants in cross-national survey research is challenging. Established techniques such as random-route sampling or random-digit-dialing are associated with high monetary costs, in particular when small migrant groups are targeted. The use of onomastic (name based) telephone sampling is a relatively cost-efficient alternative, but it relies on a number of conditions (e.g., existence of telephone directories in the respective countries and inclusion of the target population). As the use of social networking sites (SNSs) has spread around the globe in the last 20 years, the present paper investigates whether a specific SNS, Facebook, can be used to sample migrants, with the ultimate goal to supplement other approaches. This article is based on data collected as part of a survey that used Facebook advertisements to sample Polish migrants in Austria, Ireland, Switzerland, and the United Kingdom. The study succeeded in sampling a total of 1,103 individuals who completed the relatively extensive questionnaire within the field period of 8 weeks (1,100 within the 4 weeks the advertisements were placed). In contrast to most of the few other studies that tried to sample respondents with the help of Facebook advertisements, no incentives were used. With nearly all (96%) of the respondents belonging to the target population and a total sampling budget of 500 (US$557), the method can be considered both accurate and cost efficient in recruiting people from the target population. Furthermore, our results suggest that the vast majority of the sample would not have been reached if onomastic sampling had been employed.
Who is likely to be a target of online hate and extremism? To answer this question, we use an online survey (N = 963) of youth and young adults recruited from a demographically balanced sample of Americans. Adapting routine activity theory, we distinguish between actor-initiated social control (i.e., self-help), other-initiated social control (i.e., collective efficacy), and guardianship and show how self-help is positively related to the likelihood of being targeted by hate. Our findings highlight how online exposure to hate materials, target suitability, and enacting social control online all influence being the target of hate. Using social networking sites and encountering hate material online have a particularly strong relationship with being targeted with victim suitability (e.g., discussing private matters online, participating in hate online) and confronting hate also influencing the likelihood of being the target of hate speech.
This study uses multilevel generalized linear models to examine predictors of high school students’ nonresponse when using the experience sampling method (ESM), a form of momentary data collection that captures participants’ situational thoughts, feelings, and emotions. Because ESM approaches often seek to generalize and compare participants’ emotional states across days and times, it is important to understand how and when participants may miss response opportunities, and further to explore how this response bias may limit generalizability of findings. Results from this study, conducted in three mid-Michigan high schools in 2013–2014 with a sample of 141 students, indicate that time of day and day of week are significantly related to a given participant’s odds of nonresponse. Specifically, ESM "prompts" occurring after school and over the weekend had much higher odds of being missed by participants, even after controlling for other covariates such as race/ethnicity, gender, and person-level emotional trends. These findings demonstrate that day and time contextual factors are significantly related to odds of nonresponse, and researchers using these approaches to compare widely different time contexts should be mindful of possible generalizability concerns.
Videos are often used in web surveys to assess attitudes. While including videos may allow researchers to test immediate reactions, there may be issues associated with displaying videos that are overlooked. In this article, we examine the effects of using video stimuli on responses in a probability-based web survey. Specifically, we evaluate the association between demographics, mobile device usage, and the ability to view videos; differences in ad recall based on whether respondents saw a video or still images of the video; whether respondents’ complete viewing of videos is related to presentation order; and the data quality of follow-up questions to the videos as a function of presentation order and complete viewing. Overall, we found that respondents using mobile browsers were less likely to be able to view videos in the survey. Those who could view videos were more likely to indicate recall compared to those who viewed images, and videos that were shown later in the survey were viewed in their entirety less frequently than those shown earlier. These results directly pertain to the legitimacy of using videos in web surveys to gather data about attitudes.
The purpose of this study was to investigate the influence of games, where characters must overcome adversity, on player’s perceptions of their psychological resilience. Located on the PlayStation blog (blog.us.playstation.com), the online PlayStation Network (PSN) community group focuses on video gamers unique stories and experiences. Using a qualitative and exploratory design, blogs posted between March 2012 and January 2013 were analyzed for content describing experiences via gameplay that members reported made them feel more resilient. Both social and emotional aspects of resilience were discussed with players reporting game experiences had helped them feel more confident in their abilities. Many also associated themselves with the same resilient traits as their characters display in games. A range of popular off-the-shelf video games were reported as helpful in providing players with the opportunity to feel confident under pressure and, importantly, some players reported transferring these positive psychological effects to their real-world lives.
The use of social media has grown exponentially to the extent of engaging close to one third of the world’s population as of January 2016. Actually, social media statistics have been reporting an average annual increase of 10% in total number of users. These extremely impressive statistics have been triggering researchers’ interest in investigating this phenomenon and its impact on every aspect of users’ lives. Our study is an attempt to contribute to the knowledge that is building up in relation to this phenomenon by examining the relationships between the addictive use of social media, self-esteem, and satisfaction with life. To achieve this purpose, a generic questionnaire, the Social Media Addiction Questionnaire (SMAQ), was used stemming from the Facebook Intrusion Questionnaire. Respondents completed an online survey questionnaire which collected demographic information and responses to SMAQ, Rosenberg’s Self-Esteem Scale, and the Satisfaction with Life Scale. In addition to assessing SMAQ’s psychometric properties, data analyses included Pearson correlations between the variables, regression analysis, and structural equation modeling. Results showed that a one-factor model of SMAQ had good psychometric properties and had high internal consistency. As for relations, addictive use of social media had a negative association with self-esteem, and the latter had a positive association with satisfaction with life. Furthermore, path analysis showed that self-esteem mediated the effect of social media addiction on satisfaction with life.
Online data collection has become an extremely popular survey mode given its reduced cost, ease of administration, and timeliness. Although extensive research exists on the influence of e-mail invitation design characteristics to prompt survey participation, less is known about the effectiveness of e-mail reminders in prompting survey completion among nonresponders. The purpose of this study was to determine whether incorporating humor into e-mail reminders improved survey completion rates. Respondents from the Truth Initiative Young Adult Cohort (n = 2,963) who did not respond to the first standard e-mail invitation to complete their follow-up survey were randomly assigned to one of the three e-mail reminder groups: control (standard), humor only, or humor plus statistics. Those who received an initial humor plus statistics reminder e-mail received the humor only e-mail as their second reminder and vice versa. Logistic regression was used to generate the odds ratios (OR) for the probability of completing the survey after the first reminder. Results of multivariable models showed that, when collapsed together, the humor only and humor plus statistics e-mails were more effective than the control [adjusted OR (AOR) = 1.23, 95% confidence interval (CI) [1.01, 1.49], p = .05]. Receiving the humorous e-mail as the first reminder increased the odds of response to the survey by 24% (AOR = 1.24, 95% CI [1.00, 1.54], p = .04). Those entering the study at an earlier wave, nonsmokers and those living in smaller households were more likely to respond after the first reminder. A humorous reminder tailored to the voice of the audience is an easy, efficient, and effective way to increase response rates among young adults.
This study investigates the mediation impact of grade point average (GPA) and general health positive on Facebook addiction via self-esteem (SE) under the provision of active daily use of Facebook. We reached 120 participants who are college students. Our sample comprised 63 (52.5%) females and 57 (47.5%) males. We collected data through an online questionnaire. Structural equation modeling using IBM SPSS AMOS and mediation analysis were performed. The findings of the study suggested that SE is a critical and shaping construct when the decreasing impact of both GPA and general health positive on Facebook addiction is a concern. College students with low GPA and general health–positive feelings have low SE, which in turn increases the possibility of becoming a Facebook addict. Moreover, active daily use of Facebook is another factor triggering addiction. Recommendations and further research studies are presented.
This study explores how UK young adults’ exposure to social networking sites (SNSs) and attention to specific SNS content relate to their political practices. Data were collected from a diverse group of undergraduates during the 2015 General Election and Labour leadership campaign via a web survey designed with novel instruments (e.g., simulated Facebook and Twitter newsfeeds). Results indicate that regular use of varying SNSs and attention to certain political content—for example, newsfeeds about student-fee activism—have a positive weak association with off-line formal and activist participation and a considerably stronger association with online "slacktivism." Moreover, exposure to SNSs was found similarly high across respondents. However, those with typical demographic and psychographic markers of participation (e.g., upper socioeconomic status, early political socialization) showed significantly greater levels of engagement with political content and off-line and online participation. Together, these findings suggest that frequent social media consumption is linked to a minimal and narrow mobilizing impact.
Mobile phones are increasingly being used to conduct mobile computer-assisted telephone interview (CATI) surveys and some say it is just a question of time before they replace fixed phones. Although mobile phones allow their users to be called anywhere and at any time, a 100% response rate (RR) is unlikely to be achieved with a single call attempt. Callbacks are costly and delay fieldwork completion, but they are worth the effort when better overall RRs as well as those for specific subgroups of the population are obtained. Using data collected on a nationwide mobile CATI survey, this article investigates the differences between initial and callback respondents. Findings reveal that although the majority of interviews were achieved with a single call attempt, the initial sample differed from the callback sample in terms of the age and residence of respondents. Additionally, callback respondents were more likely to be interviewed outside home.
Mixed-mode surveys need to determine a number of design parameters that may have a strong influence on costs and errors. In a sequential mixed-mode design with web followed by telephone, one of these decisions is when to switch modes. The web mode is relatively inexpensive but produces lower response rates. The telephone mode complements the web mode in that it is relatively expensive but produces higher response rates. Among the potential negative consequences, delaying the switch from web to telephone may lead to lower response rates if the effectiveness of the prenotification contact materials is reduced by longer time lags, or if the additional e-mail reminders to complete the web survey annoy the sampled person. On the positive side, delaying the switch may decrease the costs of the survey. We evaluate these costs and errors by experimentally testing four different timings (1, 2, 3, or 4 weeks) for the mode switch in a web–telephone survey. This experiment was conducted on the fourth wave of a longitudinal study of the mental health of soldiers in the U.S. Army. We find that the different timings of the switch in the range of 1–4 weeks do not produce differences in final response rates or key estimates but longer delays before switching do lead to lower costs.
This article presents a continuous measure of future self-continuity (FSC-C) designed for use in web-based surveys. It allows researchers to assess on a continuous scale the similarity or connectedness that participants feel in relation to their future selves. The measure has an intuitive drag-and-drop interface, where participants can drag one circle over another circle to a certain degree of overlap to indicate closeness of the relation between their present self and their future selves. The measure is highly customizable and is therefore also attractive for researchers in other domains (e.g., to measure Inclusion of Other in the Self). In this regard, the measure is an alternative to that reported by Le, Moss, and Mashek in this journal. This article describes the motivation for the development of the measure as well as how it is constructed.
Despite the growing attention to the study of various issues concerning online self-presentation, little research has investigated the different reasons underlying the avoidance of online identity and presentation building features. Using a multistage investigation, this study has developed and validated a 25-item instrument for investigating the various reasons why young people avoid Facebook photo tagging. The instrument items were developed based on open-ended qualitative essays written by 141 Indian and Pakistani adolescents who use the Facebook photo-tagging service. From their qualitative responses, 38 items were first extracted and evaluated with 780 Indian adolescent photo taggers. This resulted in the development of a 25-item instrument which was reexamined a year later with 314 Indian adolescent and 106 young adult photo taggers. The study participants were recruited from India and Pakistan in order to address the criticism of previous Facebook research which is chiefly based on U.S.-only study samples. The developed instrument indicated six reasons: destruction of capital, dislike, worry, parental control, embarrassment, and personal appearance. The study results indicate that the developed instrument has a stable factorial structure, validity, and reliability over time. This new instrument offers various theoretical and practical implications for scholars engaged in research involving computer-mediated communication, online self-presentation, and young people.
The past decade has seen a rise in the use of online panels for conducting survey research. However, the popularity of online panels, largely driven by relatively low implementation costs and high rates of Internet penetration, has been met with criticisms regarding their ability to accurately represent their intended target populations. This criticism largely stems from the fact that (1) non-Internet (or offline) households, despite their relatively small size, constitute a highly selective group unaccounted for in Internet panels, and (2) the preeminent use of nonprobability-based recruitment methods likely contributes a self-selection bias that further compromises the representativeness of online panels. In response to these criticisms, some online panel studies have taken steps to recruit probability-based samples of individuals and providing them with the means to participate online. Using data from one such study, the German Internet Panel, this article investigates the impact of including offline households in the sample on the representativeness of the panel. Consistent with studies in other countries, we find that the exclusion of offline households produces significant coverage biases in online panel surveys, and the inclusion of these households in the sample improves the representativeness of the survey despite their lower propensity to respond.
Recruiting participants is a necessary step in many studies. With the advent of online research techniques, scientists are looking for new places where participants can be recruited online, in order to overcome the limitations of current sources and avoid the issues associated with sample overuse. The social media website "Reddit" is a potential source for recruitment, as it allows for free and rapid data collection from large samples, while enabling researchers to target specific populations when needed. The ability to recruit for free is especially important because it enables students and early career researchers, for whom even low recruitment costs can be prohibitive, to benefit from the opportunity of conducting research that they otherwise would not be able to. The current article therefore aims to bring this prospective, untapped resource to the attention of the research community. The article discusses current online recruitment sources and their limitations, provides an overview of Reddit, validates its use for research purposes, examines participation data from previous studies which recruited through Reddit, highlights its advantages and limitations as a participant pool, and suggests guidelines that can improve recruitment and retention rates for scientists looking to use Reddit for their research.
In this article, we focus on noise in the sense of irrelevant information in a data set as a specific methodological challenge of web research in the era of big data. We empirically evaluate several methods for filtering hyperlink networks in order to reconstruct networks that contain only webpages that deal with a particular issue. The test corpus of webpages was collected from hyperlink networks on the issue of food safety in the United States and Germany. We applied three filtering strategies and evaluated their performance to exclude irrelevant content from the networks: keyword filtering, automated document classification with a machine-learning algorithm, and extraction of core networks with network-analytical measures. Keyword filtering and automated classification of webpages were the most effective methods for reducing noise, whereas extracting a core network did not yield satisfying results for this case.
The number of respondents who access web surveys on a mobile device (smartphone or tablet) has been increasing rapidly over the last few years. Compared with desktop computers, mobile devices have smaller screens, different input options, and are used in a larger variety of locations and situations. The suspicion that the quality of data may suffer when online respondents use mobile devices has stimulated a growing body of research, which has mainly focused on paradata and web survey design. To investigate whether the respondents’ device affects the quality of web survey data, we examined the responses of 1,826 mobile-device and desktop participants in a political online survey that asked questions about the 2013 German federal election. To determine the reliability and validity of data submitted via mobile devices, we determined the consistency of the participants’ responses across questions and validated the responses against various internal and external criteria. Replicating previous findings, mobile-device respondents were younger and more likely to be female, and they produced higher dropout rates and longer completion times than desktop respondents. However, data produced by respondents using mobile devices were as consistent, reliable, and valid as data produced by respondents using desktop computers. These findings contradict the notion that mobile-device users compromise the reliability and validity of data collected online and suggest that researchers do not necessarily need to be afraid of the participation of mobile-device respondents in web surveys.
The article analyzes the nature of communication flows during social conflicts via the digital platform Twitter. We gathered over 150,000 tweets from citizen protests for nine environmental social movements in Chile and used a mixed methods approach to show that long-standing paradigms for social mobilization and participation are neither replicated nor replaced but reshaped. In digital platforms, long-standing communication theories, like the 1955 two-step flow model, are still valid, while direct one-step flows and more complex network flows are also present. For example, we show that it is no contradiction that social media participants mainly refer to intermediating amplifiers of communicated messages (39% of the mentions from participants go through this two-step communication flow), while at the same time, traditional media outlets and official protest voices receive 80–90% of their mentions directly through a direct one-step flow from the same participants. While nonintuitive at first sight, Bayes’s theorem allows to detangle the different perspectives on the arising communication channel. We identify the strategic importance of a group of amplifying intermediaries in local positions of the networks, who coexist with specialized voices and professional media outlets at the center of the global network. We also show that direct personalized messages represent merely 20% of the total communication. This shows that the fine-grained digital footprint from social media enables us to go beyond simplistic views of a single all-encompassing step flow model for social communication. The resulting research agenda builds on long-standing theories with a new set of tools.
Surveys have been used as main tool of data collection in many areas of research and for many years. However, the environment is changing increasingly quickly, creating new challenges and opportunities. This article argues that, in this new context, human memory limitations lead to inaccurate results when using surveys in order to study objective online behavior: People cannot recall everything they did. It therefore investigates the possibility of using, in addition to survey data, passive data from a tracking application (called a "meter") installed on participants’ devices to register their online behavior. After evaluating the extent of some of the main drawbacks linked to passive data collection with a case study (Netquest metered panel in Spain), this article shows that the data from the web survey and the meter lead to very different results about the online behavior of the same sample of respondents, showing the need to combine several sources of data collection in the future.
We examine the costs and benefits of nongovernmental organization (NGO) networking using a complex systems approach and agent-based modeling to simulate the effects of NGOs’ efforts to seek influence in policy making at home and abroad. We elaborate on the boomerang model developed by Keck and Sikkink and uncover macro-level effects of multiple NGOs networking for policy influence in multiple states around multiple positions on the same issue simultaneously. The results of our model and simulations lead us to argue that the boomerang effect has interesting unexplored implications for NGO behavior and state policy worthy of further empirical testing. We find that networking is necessary for NGOs to change state policy but leads to a higher likelihood of organizational collapse for NGOs. Although networking leads to policy change, as is well demonstrated within existing literature, our model suggests that efficacy comes at a cost to NGOs, which should make analysts and academics more ambivalent about the advisability of NGO networking.
In this article, we examine the relationship between metrics documenting politics-related Twitter activity with election results and trends in opinion polls. Various studies have proposed the possibility of inferring public opinion based on digital trace data collected on Twitter and even the possibility to predict election results based on aggregates of mentions of political actors. Yet, a systematic attempt at a validation of Twitter as an indicator for political support is lacking. In this article, building on social science methodology, we test the validity of the relationship between various Twitter-based metrics of public attention toward politics with election results and opinion polls. All indicators tested in this article suggest caution in the attempt to infer public opinion or predict election results based on Twitter messages. In all tested metrics, indicators based on Twitter mentions of political parties differed strongly from parties’ results in elections or opinion polls. This leads us to question the power of Twitter to infer levels of political support of political actors. Instead, Twitter appears to promise insights into temporal dynamics of public attention toward politics.
Surveys completed on mobile web devices (smartphones) have been found to take longer than surveys completed on a PC. This has been found both in surveys where respondents can choose which device they use and in surveys where respondents are randomly assigned to devices. A number of potential explanations have been offered for these findings, including (1) slower transmission over cellular or Wi-Fi networks, (2) the difficulty of reading questions and selecting responses on a small device, and (3) the increased mobility of mobile web users who have more distractions while answering web surveys. In a secondary analysis of student surveys, we find that only about one-fifth of the time difference can be accounted for by transmission time (between-page time) with the balance being within-page time differences. Using multilevel models, we explore possible page-level (question-level) and respondent-level factors that may contribute to the time difference. We find that much of the time difference can be accounted for by the additional scrolling required on mobile devices, especially for grid questions.
In light of waning interpersonal contact in America, scholars have turned their attention to social network sites and the opportunities these provide for building and maintaining social relationships. The present study adds to this research, using national survey data from U.S. adults to examine how motivated use of Facebook for expanding and diversifying personal networks might revitalize real-world efforts of sociability for users, and returns to social capital that come by way of them. Results support our overall model relating weak-tie interactions to generalized trust. More importantly, when we use it to compare more and less sociable Facebook users, we find meaningful differences in the strength of the relationships between variables in the model. In particular, for more sociable users, interacting with weak ties was related to greater civic participation and increased feelings of generalized trust. Access to bridging social capital was a larger source of generalized trust for more sociable users as well. Ultimately, our findings suggest that sociability on sites like Facebook can facilitate the development of communication competence, where users who make a concerted effort of expanding and diversifying their personal networks come to interact with a wider array of individuals, and learn how to do so more effectively.
A key goal of survey interviews is to collect the highest quality data possible from respondents. In practice, however, it can be difficult to achieve this goal because respondents do not always understand particular survey questions as designers intended. Researchers have used a variety of indicators to identify and predict respondent confusion and difficulty in answering questions in different modes. In web surveys, it is possible to automatically detect response difficulty in real time. The research to date has focused on response latencies—mostly long response times—as evidence of difficulty. In addition to response latencies, however, web surveys offer rich behavioral data, which may predict respondent confusion and difficulty more directly than response times. This article focuses on one such behavior, mouse movements. We examine a set of mouse movements participants engage in when answering questions about experimental scenarios whose difficulty has been manipulated (as confirmed by respondent ratings). This approach makes it possible to determine which movements are general movements, demonstrating how a person interacts with a computer, and which movements are related to response difficulty. We find not only that certain mouse movements are highly predictive of difficulty but also that such movements add considerable value when used in conjunction with response times. The approach developed in this article may be useful in delivering help to confused respondents in real time and as a diagnostic tool to identify confusing questions.
Recent innovations in conflict and computer research favor generating massive event data using automated coding protocols. Unfortunately, these approaches almost exclusively rely on English-language sources, thus causing problems of coverage bias and misleading inferences. In an effort to attenuate Anglocentrism in event data, we introduce Eventus ID, new software for supervised event coding from text written in Spanish. Drawing on real news reports, the application generates daily georeferenced data on how the military fights organized criminals in Mexico. Performance metrics show that Eventus ID is almost as accurate as humans for coding event data.
We used the model of prospective memory and habit development to derive recommendations for designing behavior-change campaigns that used prompts or household visits as reminders. We followed an exemplary procedure comprising the calibration of the model, based on 48 time series gathered during a campaign promoting recycling habits and a systematic exploration of the solution space. For the parameter estimation, an algorithm was developed that worked at two levels. A higher level algorithm optimized parameters that were set to equal values for all agents, whereas a lower level algorithm estimated the values of agent-specific parameters for each agent separately, using the parameter values of the higher level algorithm for the other parameters. This procedure resulted in an excellent fit of the model to the data (R 2 = 75%) For the systematic exploration, an indicator expressing campaign effects in one value was defined and the following findings could be derived. Activities should focus on the first week of a campaign. Follow-up visits or refreshing of prompts should be done within 4 days after the initial visit. Later activities, such as additional visits or refreshing of prompts, bring little further effects. Investing heavily in the design of the prompts for improving their salience is only worthwhile in populations with a low commitment to perform the behavior. Furthermore, covering more than 10% of the places where the target behavior should be performed with prompts mostly does not lead to additional effects to make it worthwhile.
Citizens’ engagement is considered as one of the important dimensions for the development of smart cities since, in the vision of a city of the future (smart city), citizens will be more and more involved in the decision-making process of different issues related to the development of a city. In this context, policy makers face a decision problem where they have to integrate a new dimension, which is the voice of the citizens’ decision. This article proposes a tool based on multicriteria decision making methods to provide decision makers with the best alternative(s) that are based on citizens’ opinions. In order to tackle the potential interdependencies between criteria and also between alternatives in the selection process, we apply a hybrid model integrating the analytical network process and an extended version of technique for order performance by similarity to ideal solution to support group decision-making. The proposed model is applied in the context of participatory budgeting (PB) where citizens decide on the projects in which the money can be invested. This process is complex since it encompasses multiple interdependent criteria that may be conflicting with each other and that are used to take decisions. To illustrate our approach, we will apply the proposed technique for the case study of La Marsa, a city in the north of the capital Tunis (Tunisia) that adopted, since 2014, a PB strategy in which citizens proposed alternatives on how an amount of money can be used to lighten specific streets in the city.
Trauma-based interventions are common in mental health practice, and yet there is a gap in services because social media has created new ways of managing trauma. Practitioners identify treatments for traumatic experiences and are trained to implement evidence-based practices, but there is limited research that uses social media as a data source. We use a case study to explore over 400 Twitter communications of a gang member in Chicago’s Southside, Gakirah Barnes, who mourned the death of her friend on Twitter. We further explore how, following her own death, members of her Twitter network mourn her. We describe expressions of trauma that are difficult to uncover in traditional trauma-based services. We discuss practice and research implications regarding using Twitter to address trauma among gang-involved youth.
Social media have changed the way citizens, journalists, institutions, and activists communicate about social and political issues. However, questions remain about how information is diffused through these networks and the degree to which each of these actors is influential in communicating information. In this study, we introduce two novel social network measures of connection and information diffusion that help shed light on patterns of political communication online. The Audience Diversity Score assesses the diversity of a particular actor’s followers and identifies which actors reach different publics with their messages. The Communication Connector Bridging Score highlights the most influential actors in the network who are potentially able to connect different spheres of communication through their information diffusion. We apply and discuss these measures using Twitter data from the discussion regarding the Transatlantic Trade Investment Partnership in Europe. Our results provide unique insights into the role various actors play in diffusing political information in online social networks.
This special issue of the Social Science Computer Review provides a sample of the latest strategies employing large data sets in social media and political communication research. The proliferation of information communication technologies, social media, and the Internet, alongside the ubiquity of high-performance computing and storage technologies, has ushered in the era of computational social science. However, in no way does the use of "big data" represent a standardized area of inquiry in any field. This article briefly summarizes pressing issues when employing big data for political communication research. Major challenges remain to ensure the validity and generalizability of findings. Strong theoretical arguments are still a central part of conducting meaningful research. In addition, ethical practices concerning how data are collected remain an area of open discussion. The article surveys studies that offer unique and creative ways to combine methods and introduce new tools while at the same time address some solutions to ethical questions.
There are three issues that are crucial to advancing our academic understanding of smart cities: (1) contextual conditions, (2) governance models, and (3) the assessment of public value. A brief review of recent literature and the analysis of the included papers provide support for the assumption that cities cannot simply copy good practices but must develop approaches that fit their own situation (contingency) and concord with their own organization in terms of broader strategies, human resource policies, information policies, and so on (configuration). A variety of insights into the mechanisms and building blocks of smart city practices are presented, and issues for further research are identified.
Most of the definitions of a "smart city" make a direct or indirect reference to improving performance as one of the main objectives of initiatives to make cities "smarter". Several evaluation approaches and models have been put forward in literature and practice to measure smart cities. However, they are often normative or limited to certain aspects of cities’ "smartness", and a more comprehensive and holistic approach seems to be lacking. Thus, building on a review of the literature and practice in the field, this paper aims to discuss the importance of adopting a holistic approach to the assessment of smart city governance and policy decision making. It also proposes a performance assessment framework that overcomes the limitations of existing approaches and contributes to filling the current gap in the knowledge base in this domain. One of the innovative elements of the proposed framework is its holistic approach to policy evaluation. It is designed to address a smart city’s specificities and can benefit from the active participation of citizens in assessing the public value of policy decisions and their sustainability over time. We focus our attention on the performance measurement of codesign and coproduction by stakeholders and social innovation processes related to public value generation. More specifically, we are interested in the assessment of both the citizen centricity of smart city decision making and the processes by which public decisions are implemented, monitored, and evaluated as regards their capability to develop truly "blended" value services—that is, simultaneously socially inclusive, environmentally friendly, and economically sustainable.
Social media offer an avenue for the formation of citizen-driven global networks that are vital to mobilizing international support and curating global public discourse in social movements. This study looks into the global flow of information and communication about Hong Kong's Occupy Central Movement with a focus on the country/territory-level international network that emerged on Twitter. Drawing on the world systems theory and the literature on social movement, it examines whether the globalization of a local social movement via social media is circumscribed by the existing order of the world system (i.e., from the developed core countries/territories to the developing peripheral). It focuses its analysis on the network structure and the predictors of countries/territories’ centrality in the network. Findings of the social network analysis show that the structure of the international network still follows the existing order of the world system to a large extent. It is further supported by the result of the multivariate analysis that national income, a widely used benchmark for determining a country/territory's position in the world economy, is significantly and substantially related to centrality. However, national income does not have the largest predicting power. Instead, a country/territory's level of political grievances is found to be the strongest predictor. In addition, countries/territories with high Internet penetration rates tend to have high-centrality scores, and yet the effect size is smaller than the other predictors.
In November 9, 2014, the Catalan government called Catalan people to participate in a straw poll about the independence of Catalonia from Spain. This article analyzes the use of Twitter between November 8 and 10, 2014. Drawing on a methodology developed by Guerrero-Solé, Corominas-Murtra, and Lopez-Gonzalez, this work examines the structure of the retweet overlap network (RON), formed by those users whose communities of retweeters have nonzero overlapping, to detect the community structure of the network. The results show a high polarization of the resulting network and prove that the RON is a reliable method to determinate network community structures and users’ political leaning in political discussions.
The term "gamification" is used for a wide variety of techniques aimed to increase respondent engagement while filling out web surveys. Suggested approaches range from rephrasing questions to sound more game-like to embedding the entire survey into a game where respondent avatars adventure through a fantasy land while answering survey questions. So far, only a few experimental studies regarding the influence of gamification on survey responding have been published in peer-reviewed journals. This article systematically reviews the current research literature on gamification in surveys by first answering the question as to what gamification entails in the context of web surveys by identifying relevant gamification elements. Next, the article discusses how these elements could influence survey data quality using the Total Survey Error framework. Finally, a systematic review of empirical evidence on gamified surveys from published and unpublished studies is provided. While most studies found in our literature review reported a positive effect of using game elements, such as challenges, story/narrative, rewards, goals/objectives, and badges, on psychological outcomes among survey respondents (e.g., fun, interest, satisfaction), the influence of these elements on behavioral outcomes (e.g., completion and break-offs, item omission, satisficing, responses) and, therefore, survey quality is more unclear. This article informs survey researchers and practitioners of the current state of research on survey gamification and identifies potential areas for future research.
Does the opportunity to deliver visual instead of verbal stimuli of political knowledge to respondents in web-based surveys make a difference in terms of data quality? For instance, does the presentation of visual knowledge items reduce cheating, that is, looking up the answer via the Web? And do visual and verbal stimuli capture the same underlying construct? To test whether the use of visuals to measure political knowledge effectively makes a difference, we administer a question form experiment in an online survey of the German Longitudinal Election Study. Respondents are randomly assigned to one of two question formats—visual or verbal—and are asked to solve a set of eight questions on political leaders and their offices. The instruments are validated based on nonparametric item response theory and analyses of response latency. While there is no clear evidence for cheating behavior under either of the conditions, both instruments form strong knowledge scales. Results from a regression analysis indicate that the scales provide measures of closely related but not identical concepts.
The attention for Smart governance, a key aspect of Smart cities, is growing, but our conceptual understanding of it is still limited. This article fills this gap in our understanding by exploring the concept of Smart governance both theoretically and empirically and developing a research model of Smart governance. On the basis of a systematic review of the literature defining elements, aspired outcomes and implementation strategies are identified as key dimensions of Smart governance. Inductively, we identify various categories within these variables. The key dimensions were presented to a sample of representatives of European local governments to investigate the dominant perceptions of practitioners and to refine the categories. Our study results in a model for research into the implementation strategies, Smart governance arrangements, and outcomes of Smart governance.
Smart cities (SCs) are a recent but emerging phenomenon, aiming at using high technology and especially information and communications technology (ICT) to implement better living conditions in large metropolises, to involve citizens in city government, and to support sustainable economic development and city attractiveness. The final goal is to improve the quality of city life for all stakeholders. Until now, SCs have been developing as bottom-up projects, bringing together smart initiatives driven by public bodies, enterprises, citizens, and not-for-profit organizations. However, to build a long-term smart strategy capable of producing better returns from investments and deciding priorities regarding each city, a comprehensive SC governance framework is needed. The aim of this paper is to collect empirical evidences regarding government structures implemented in SCs and to outline a framework for the roles of local governments, nongovernmental agencies, and administrative officials. The survey shows that no consolidated standards or best practices for governing SCs are implemented in the examined cities; however, each city applies its own governance framework. Moreover, the study reveals some interesting experiences that may be useful for involving citizens and civil society in SC governance.
Facebook is expected to facilitate more equal participation in civic engagement across genders and countries. With the use of a big data tool (Wisdom), we explored gender disparities in various Facebook liking practices concerning expressions of civic engagement among 21,706,806 Facebook users in 10 countries across Asia, Africa, the Americas, and Europe. We observed distinct patterns with regard to civic and political expressions on Facebook, with males drawn more toward politically and information-oriented liking practices when compared to females. Moreover, females (aged 13–28 years) in Europe and the Americas are more likely than males to support humanitarian aid and environmental issues on Facebook. This latter finding was not evident in Asia and Africa, where males are more active in liking all forms of civic expressions on Facebook. In conclusion, this study shows that the gender differences in civic engagement that exist offline to a large degree are replicated and reinforced on Facebook.
This article introduces a novel method that combines a "big data" measurement of the content of individuals’ Facebook (FB) news feeds with traditional survey measures to explore the antecedents and effects of exposure to news and politics content on the site. Drawing on recent theoretical and methodological advances, we demonstrate how such a hybrid approach can be used to (a) untangle distinct channels of public affairs content within respondents’ FB news feeds, (b) explore why respondents vary in the extent to which they encounter public affairs content on the site, and (c) examine whether the amount and type of public affairs content flows in one’s FB is associated with political knowledge and participation above and beyond self-report measures of news media use.
Environmental sustainability is a critical global issue that requires comprehensive intervention policies. Viewed as localized intervention policy implementations, smart cities leverage information infrastructures and distributed renewable energy smart micro-grids, smart meters, and home/building energy management systems to reduce city-wide carbon emissions. However, theory-driven smart city implementation research is critically lacking. This theory-building case study identifies antecedent conditions necessary for implementing smart cities. We integrated resource dependence, social embeddedness, and citizen-centric e-governance theories to develop a citizen-centric social governance framework. We apply the framework to a field-based case study of Japan’s Kitakyushu smart community project to examine the validity and utility of the framework’s antecedent conditions: resource-dependent leadership network, cross-sector collaboration based on social ties, and citizen-centric e-governance. We conclude that complex smart community implementation processes require shared vision of social innovation owned by diverse stakeholders with conflicting values and adaptive use of informal social governance mechanisms for effective smart city implementation.
The work we will be discussing here explores how government, industry, the university, and the citizens of a city can arrive through a participatory design approach at an increased and mutual understanding and a shared vision of a desired smart city of the future. Elaborating upon insights from transition management studies and from the quadruple-helix knowledge production model, our work proposes a participatory approach for prototyping future cities that embraces practice-oriented design research activities and thus aims for practical impact. We will report on two cases, GovJam and Hackday Data of the Crowds, in which stakeholders were able to acquire through participatory prototyping an understanding of the possibilities of technology in city services of the future. Results from these sessions show that participating stakeholders indeed gained a new perspective upon issues facing the city, due to an increased awareness and understanding of, and empathy for, the interests of other stakeholders. We also found indications that transfer of knowledge was taking place from the prototyping sessions to the daily practice of participants working in the public sector.
This article explores how individuals use online coping strategies after experiencing a negative life event. Many studies have shown that online coping is of rising importance. However, these studies have not provided all pieces of the puzzle because they tend to focus on one particular online venue (e.g., an online support group or social network site [SNS]) and on a limited number of coping strategies. This article aims to provide a more complete picture, by simultaneously examining multiple online and off-line coping strategies, using a survey administered to a representative sample of the 16+ population of the Netherlands. Furthermore, we analyze what kind of Internet activities are related to online coping and whether online coping is associated with well-being. Some 57% of our sample mentioned some form of online coping. Using the Internet for mental disengagement, active coping and planning were the most reported online coping strategies, whereas strategies aimed at emotional coping were reported less frequently. Online coping encompassed several activities: online gaming, which was associated with mental disengagement; searching for information, which was associated with problem-focused coping; and SNS and online support groups, which were associated with mental disengagement, problem-focused coping, and socioemotional coping. Finally, we examined the correlations between online coping and well-being. Controlling for off-line coping, we found online mental disengagement and online socioemotional coping to be inversely related to life satisfaction, self-esteem, and optimism, whereas correlations between online problem-focused coping and well-being were nonsignificant. The implications of these findings are discussed.
This brief article weighs in on a pedagogical debate concerning the didactic usefulness of an online international relations computer simulation called Statecraft. In a 2014 article, Gustavo Carvalho, a teaching assistant at the University of Toronto, claimed, based on the results of a survey he administered to an international relations class that used Statecraft, that the simulation had little to offer students as a teaching tool. In a rebuttal, Statecraft creator Jonathan Keller took Carvalho to task for not employing the simulation properly, which biased his results. While Carvalho only presented results for one class, the present analysis reports on survey responses of students over six different classes which used Statecraft from 2013 to 2014. The results call into question Carvalho’s findings and suggest that the context and curriculum matter as much as the simulation itself when judging the pedagogical value of computer-mediated learning tools.
Research on Smart Cities has come of age. Intense discussion on this topic has been ongoing for years, and the academic prominence of this concept has also engendered several policy initiatives inspired by this label at different administrative levels. However, to date, no large-scale evaluation of the relationship between urban smartness and smart urban policies has been attempted. This article aims at filling this gap. By building on a solid definition of Smart Cities, the article tests the empirical relationship between urban smartness and the intensity of Smart City policies. A novel data set on four different types of policies and smart urban characteristics is assembled for 314 European Union cities. Empirical results suggest that Smart City policies are more likely to be designed and implemented in cities that are already endowed with smart characteristics. Our findings also point to a higher probability that Smart City policies are implemented in denser and wealthier urban areas. These empirical results call for further research on the real effects of actual implemented Smart City policies, with the aim to verify the potential of this policy concept as an overall urban development model encompassing the main drivers of endogenous urban growth.
The growing participation in social networking sites is altering the nature of social relations and changing the nature of political and public dialogue. This article contributes to the current debate on Web 2.0 technologies and their implications for local governance through the identification of governance models to be adopted by local governments if Web 2.0 technologies are implemented for providing public services. Also, this article analyzes whether the political competition could be an attribute that could explain the governance models to be adopted by municipalities. To achieve this aim, an e-survey during the period of May–July 2014 has been performed by policy makers responsible of strategies for e-government in Spanish municipalities. Findings indicate that policy makers are mainly prone to implement Web 2.0 technologies under the "Bureaucratic Model" framework, keeping the leading role in this implementation. Nonetheless, political competition seems to be essential to understand the findings of this article. Thus, majority governments are prone to implement collaborative models of governance, whereas minority governments are in favor to implement noncollaborative models of governance.
The aim of this article is to engage with problems of sampling and completeness currently discussed within data science through the specific example of conversations in Twitter. Some of the difficulties involved in Twitter concern restrictions laid out by platform owners, restrictions that make it difficult for researchers to collect complete conversations. A contribution is made through the development of a method for collecting and analyzing follow-on conversations around a set of hashtags. This was made possible through the simultaneous tracking of a set of hashtags and prominent participants in the conversation. The full set of tweets was compared to the subset of tweets including either of the selected hashtags. Including follow-on conversation increased the set of tweets by 56% and the set of tweeting users by 17%. It is also shown that different network analysis techniques and filtering options give different results with regard to prominent users.
Although several models in the literature analyze the dynamics of opinion formation, less attention has been paid to explain how the structure of social networks and their contextual circumstances can influence the course of minority public opinions. This work aims to pose three basic questions: (1) how the structure of social networks can affect the spread of minority opinion, (2) how committed agents influence this process, and (3) how mass media action, as a contextual factor, can vary different agents’ opinions and network composition. Agent-based modeling is used to create a network model of preferential attachment to explore how phenomena of minority opinion spreading can evolve under different simulated scenarios. This study shows that the success of minority opinions depends on network structure and composition and thus on external factors such as mass media action that can mediate the strength of these internal determinants. Although people tend to remain silent when they feel that their opinions are in the minority, our findings suggest that prevailing majority opinion may be promptly replaced by what was formerly minority opinion if core agents in the network structure and/or external sources support this view.
Social network site (SNS) data provide scholars with a plethora of new opportunities for studying public opinion and forecasting electoral outcomes. While these are certainly among the most promising big data applications in political science research, a series of pioneering studies have started to uncover the vast potential of such data to estimate the policy positions of political actors. Adding to this emerging strand in the scholarly literature, the present article explores the validity of (individual) policy positions derived from the social network structure of the microblogging platform Twitter. At the aggregate party level, cross-validation with external data sources suggests that SNS data provide valid policy position estimates. In contrast, the empirical analysis reveals only a moderate connection between individual policy positions retrieved from the social network structure and those retrieved from members of parliament individual voting record. These results thus highlight the potential as well as important limitations of SNS data in indicating the policy positions of political parties and individual legislators.
Using 414,322 tweets drawn from 143,404 individual Twitter users located in all 435 U.S. congressional districts, this study employed big data and automated content analysis techniques to explore the degree to which socioeconomic status (SES), social capital potential (the degree to which a congressional district has the potential for interconnected citizen networks), and in-district partisan polarization were associated with incivility on Twitter during the 2012 presidential election. Broadly speaking, and with some exceptions, the results indicated that election oriented incivility on Twitter was highest in districts that had low SES indicators, low levels of social capital potential, and low levels of partisan polarity. In its sum, this study shows how large social data sets (i.e., the Census) can be combined with big data to explain social phenomena.
Graphical virtual worlds add two new layers to the old question what determines friendship formation. First, it is possible to distinguish between off-line (player) and online (avatar) characteristics. Second, these environments offer new possibilities for studying friendship formation. By tracking friendship requests and their acceptance rate, researchers are able to distinguish between with whom players want to become friends and with whom they actually do become friends. This article examined friendship formation in Timik, a graphical virtual world targeted at Polish teenagers. Homophily, preferential attachment and status were tested as possible underlying mechanisms. Results showed that preferential attachment and status drove invitations: Players wanted to become friends with high-status players. However, high-status players were also more likely to reject offers. Homophily only played a minor role. Players preferred players of the same avatar class and similar age but of the opposite sex. Too similar avatars were disliked. The results are discussed in the light of the generalizability of off-line theories of friendship formation to online worlds.
This article investigates how webpages shown to respondents before they enter a self-administered survey impact whether and how they respond. Using the SurveyMonkey "end page," a page that is displayed nearly 3 million times daily to survey respondents who have completed a user-created survey, this article examines whether the type of image and text that are displayed on the end page has a large impact on survey participation, whether different images/texts appeal to different types of respondents, and whether they render different substance responses. The topic of the survey is about the U.K. 2015 General Election. The findings show that when a concrete image/text combination is displayed, the click rate is lower than more general and abstract image/text combinations. The completion rates across different webpages are similar. We also find that the sample compositions and selected survey responses differ by different end pages. As a last step, we conducted poststratification in each condition separately to produce estimates that match known population proportions for selected demographic characteristics. After weighting adjustment, the differences in substantive responses disappeared or reduced, suggesting that different people drawn into the survey through different webpages contribute to the different substantive responses.
Qualitative data analysis software (QDAS) programs are well-established research tools, but little is known about how researchers use them. This article reports the results of a content analysis of 763 empirical articles, published in the Scopus database between 1994 and 2013, which explored how researchers use the ATLAS.ti™ and NVivo™ QDAS programs.* The analysis specifically investigated who is using these tools (in terms of subject discipline and author country of origin), and how they are being used to support research (in terms of type of data, type of study, and phase of the research process that QDAS were used to support). The study found that the number of articles reporting QDAS is increasing each year, and that the majority of studies using ATLAS.ti™ and NVivo™ were published in health sciences journals by authors from the United Kingdom, United States, Netherlands, Canada, and Australia. Researchers used QDAS to support a variety of research designs and most commonly used the programs to support analyses of data gathered through interviews, focus groups, documents, field notes, and open-ended survey questions. Although QDAS can support multiple phases of the research process, the study found the vast majority of researchers are using it for data management and analysis, with fewer using it for data collection/creation or to visually display their methods and findings. This article concludes with some discussion of the extent to which QDAS users appear to have leveraged the potential of these programs to support new approaches to research.
Swearing, the use of taboo languages tagged with a high level of emotional arousal, has become commonplace in contemporary political culture. The current study attempts to understand the ways in which swearing influences citizen-to-citizen news commenting online. Based on a large corpus of the 2-month user comments from 26 news websites in South Korea, the study examines swearing effects as well as its interplay with anonymity on garnering public attention and shaping other users’ perceptions of the comments. Findings suggest that swearing generally has a positive effect on increasing user attention to comments as well as gaining other users’ approvals. Comparisons between political and nonpolitical topics further suggest that swearing effect on gaining public attention is particularly prominent for political discussions. In contrast, the magnitude of change toward positive valence in public perception to comments is much greater for nonpolitical topics than for politics. From the findings, we conclude that an acceptable degree of swearing norms in online discussions vary across news topical arenas. The results also lead to discussions about the possibility of like-minded exposure to political comments as a default condition for online discussions. Finally, the study highlights the role of high-arousal emotions in shaping discursive participation in contemporary networked sociodigital environment.
In questionnaire pretesting, supplementing cognitive interviewing with eye tracking is a promising new method that provides additional insights into respondents’ cognitive processes while answering survey questions. When incorporating eye tracking into cognitive interviewing, two retrospective probing techniques seem to be particularly useful. In the first technique—retrospective probing—participants complete an online questionnaire, while cognitive interviewers monitor participants’ eye movements in an adjacent room and note down any peculiarities in their reading patterns. Afterward, the interviewers ask targeted probing questions about these peculiarities in a subsequent cognitive interview. In the second technique—gaze video cued retrospective probing—respondents are additionally shown a video of their eye movements during the cognitive interview. This video stimulus is supposed to serve as a visual cue that may better enable respondents to remember their thoughts while answering the questions. We examine whether one of the two techniques is more effective when it comes to identifying problematic survey questions. In a lab experiment, participants’ eye movements (n = 42) were tracked while they completed six questions of an online questionnaire. Simultaneously, their reading patterns were monitored by an interviewer for evidence of response problems. After completion of the online survey, a cognitive interview was conducted. In the retrospective probing condition, probing questions were asked if peculiar reading patterns were observed during the eye-tracking session (e.g., rereadings of specific words or text passages). In the other condition, participants were shown a video of their recorded eye movements, in addition to receiving probing questions about the questions displayed. Results show that both techniques did not differ in terms of the total number of problems identified. However, gaze video cued retrospective probing identified fewer unique problems and fewer types of problems than pure retrospective probing.
Many cite the growing tendency of political parties to nominate ideologically extreme candidates in U.S. primary elections as a reason for increasing congressional polarization. However, a lack of quantitative data on candidate ideology makes this claim difficult to test. We propose a unique solution to this problem that exploits data from the increasingly popular realm of social media by estimating ideal points for candidates for the U.S. Senate based on the patterns of connections in their Twitter social network. We identify a latent ideological dimension from the matrix of following relations, which corresponds closely to roll call–based estimates for congressional officeholders. Controlling for other relevant factors, we find support for the hypothesis that ideological extremity is advantageous in party primaries.
Methods to automatically analyze media content are advancing significantly. Among others, it has become increasingly popular to analyze the framing of news articles by means of statistical procedures. In this article, we investigate the conceptual validity of news frames that are inferred by a combination of k-means cluster analysis and automatic sentiment analysis. Furthermore, we test a way of improving statistical frame analysis such that revealed clusters of articles reflect the framing concept more closely. We do so by only using words from an article’s title and lead and by excluding named entities and words with a certain part of speech from the analysis. To validate revealed frames, we manually analyze samples of articles from the extracted clusters. Findings of our tests indicate that when following the proposed feature selection approach, the resulting clusters more accurately discriminate between articles with a different framing. We discuss the methodological and theoretical implications of our findings.
This study used in-depth observations to investigate the differences in digital literacy among African American young adult Internet users. Sampled Internet users participated in one-to-one real-time observation sessions, in which each user completed Internet-related functions in two dimensions: (1) information search and (2) privacy protection. Observations recorded whether and how quickly each participant completed the assigned tasks. We found that few participants were able to complete assigned information tasks and could control basic features in browser settings. The findings also indicated that levels of digital literacy were more related with their online access experiences than with sociodemographic characteristics. We discussed policy implications of the findings and suggested potential areas of policy concern and remedies.
Social media use in government has gained a rapid growth in the last few years around the world. China has witnessed a boom in social media use in government, especially government microblogging. In this study, we employ social representation theory as the primary theoretical lens to investigate Chinese government microblogging. We hope the employment of social representation theory could help us overcome the limitation that previous studies focused on the technology and government side. Interviewing data are drawn from a number of Chinese citizens for eliciting their understandings of Chinese government microblogging, followed by structural analytical procedure on the collected data. The social representation elements are obtained and presented in a map. The findings indicate that (1) social media use in government in China is at the stage of fast growth but at low interaction level; (2) governance and social media user experiences are two new but significant concepts that might have been missed in literature; (3) government microblogging does improve citizens’ perceptions toward government; however, the final outcomes like trust and accountability cannot be achieved by relying on social media use in government alone. Theoretical contributions and practitioner implications are then discussed, followed by the limitations. Finally, we present the concluding remarks for this study.
Many democratically elected representative governments around the world require the formation of a coalition to create a government that is expected to be durable and stable. Creating such a coalition is far from trivial. This research describes a computerized coalition formation decision support system that attempts to meet this challenging task and formally rank possible coalitions. We use theories from political science and utilize insights from artificial intelligence to build the tool. We demonstrate the tool’s utility and validity empirically by comparing historical coalitions to predictions made by the tool. Tests show that we are able to recommend quite accurately durable coalitions and assess which coalitions would most likely be unstable.
This study investigated how messaging app Line’s character sticker use may contribute to the perception of intimate experience and enhance relationship satisfaction in both positive and negative emotion situations. A 2 (situation valence: positive emotion and negative emotion) x 3 (response style: text, sticker, and text and sticker) x 3 (scenario: career, romance, and education) mixed design, with situation valence and response style between-subjects variables and scenario a within-subjects variable, was employed. The results revealed the combination of a text and sticker response to a partner’s disclosure can produce the highest level of intimate experience, followed by text- and sticker-only responses. It further suggests that the cartoon-like Line sticker may better convey positive than negative emotions because the detailed illustration is more similar to real-life nonverbal behavior expressing humor and happiness and that may facilitate imagined closeness between communication partners when moving through space. The hyperpersonal affordance of text-based messages to foster relationship may be further distinguished between the cognitive and the affective levels in the messaging app context.
Through examining established and evolving conceptions of intelligence across natural and social science and applying them to Wikipedia, this article argues that the world’s largest encyclopedia and broadest implementation of the wiki is an online instance of collective intelligence (CI), as it fits key models for this concept. Further, by relying on sociotechnical ensembles of human intelligence, programmed bots, social bureaucracy, and software protocols, a more humanistic CI, as proposed by Lévy, is realized in a virtual knowledge space that embodies information as both product and process while empowering its community to explore the cultural possibilities of its collectivism.
The Internet is considered an attractive option for survey data collection. However, some people do not have access to it. One way to address this coverage problem for general population surveys is to draw a probabilistic sample and provide Internet access to the selected units who do not have it and accept to participate. This is what the knowledge panel and the Longitudinal Internet Studies for the Social sciences (LISS) panel do. However, a selection effect is still possible. Units without previous Internet access might refuse to participate in a web panel, even if provided with the necessary equipment. Thus, efforts to provide the necessary equipment may not be worth it. This article investigates the gain in terms of representativeness of offering the equipment to non-Internet units in a web panel using tablets: the French Longitudinal Internet Studies for the Social Sciences panel. We find that the number of non-Internet units who accept to participate is low. This is not only due to the fact that their response rates are lower but also to the small proportion of non-Internet units in the French population. In addition, they participate less in given surveys once they become panelists. At the same time, they are very different from the Internet units. Therefore, even if because of the small number of units, the overall gain in representativeness is small, there are a few important variables (e.g., education) on which their inclusion yields a more representative sample of the general population.
Interview duration is an important variable in web surveys because it is a direct measure of the response burden. In this article, we analyze the effects of the survey design, respondent characteristics, and the interaction between these effects on interview duration. For that purpose, we applied multilevel analysis to a data set of 21 web surveys on political attitudes and behavior. Our results showed that factors on both levels, the individual and the survey level, had effects on interview duration. However, the larger share of the variation in interview duration is explained by the characteristics of the respondents. In this respect, we illustrate the impact of mobile devices and panel recruitment on interview duration. In addition, we found important relationships between the respondents’ attitudes and how a web survey is designed: Highly motivated respondents spent significantly more time answering cognitively demanding questions than less motivated respondents. When planning a survey, not only the number and formats of questions need to be taken into account but also the expected sample composition and how the participants will respond to the design of the web survey.
This article investigates item nonresponse in open-ended survey questions because such item nonresponse is much higher than in closed questions. The difference is a result of the higher cognitive burden placed on the respondent. To study item nonresponse, we manipulate different questionnaire design characteristics, such as the size of the answer box and the inclusion of motivation texts, as well as respondent-specific characteristics, in a randomized web experiment using a student sample. The results show that a motivation text increases the frequency of responses to open-ended questions for both small and large answer boxes. However, large answer boxes earn higher item nonresponse than small answer boxes regardless of the usage of a motivation text. In addition, gender and the respondent’s field of study affected the answering of open-ended questions; being a woman or studying social sciences increased the frequency of a response. As the major finding and in contrast to previous findings, our results indicate that particularly large answer boxes should be avoided, because they reduce respondents’ willingness to respond.
Evaluating the quality of the data is a key preoccupation for researchers to be confident in their results. When web surveys are used, it seems even more crucial since the researchers have less control on the data collection process. However, they also have the possibility to collect some paradata that may help evaluating the quality. Using this paradata, it was noticed that some respondents of web panels are spending much less time than expected to complete the surveys. This creates worries about the quality of the data obtained. Nevertheless, not much is known about the link between response times (RTs) and quality. Therefore, the goal of this study is to look at the link between the RTs of respondents in an online survey and other more usual indicators of quality used in the literature: properly following an instructional manipulation check, coherence and precision of answers, absence of straight-lining, and so on. Besides, we are also interested in the link of RT and the quality indicators with respondents’ auto-evaluation of the efforts they did to answer the survey. Using a structural equation modeling approach that allows separating the structural and the measurement models and controlling for potential spurious effects, we find a significant relationship between RT and quality in the three countries studied. We also find a significant, but lower, relationship between RT and auto-evaluation. However, we did not find a significant link between auto-evaluation and quality.
The purpose of this study is to analyze the impact of homophily on diffusion over social networks. An agent-based simulation model is developed to serve as the experimental ground for this analysis. Diffusion dynamics of a nonsticky innovation is investigated by varying homophily levels in the social network depicted in the model as the primary control variable. First of all, the results show that homophily is self-reinforcing. Second, starting from a nonhomophilous network, early increases in the level of homophily have a positive effect on the extent of diffusion, whereas further increases have a negative impact. Finally, several local minima and maxima are observed in the relation between the homophily level and the extent of diffusion. Our analysis focuses on node properties such as connectedness and average degrees in order to explain the observed regular relationship between homophily and diffusion. We argue that (i) homophily increases the connectedness of different status groups separately and (ii) increasing levels of homophily decreases the marginal importance of a single homophilous tie by increasing the sources of valuable information. Future research involves investigating the coevolution of social behavior and networks by allowing the adopted innovation to lead to value homophily, exploration of different diffusion initiation types, and different adoption heuristics.
The purpose of this study is to explore the roles of psychological attributes (such as shyness and loneliness) and smartphone usage patterns in predicting smartphone addiction symptoms and social capital. Data were gathered from a sample of 414 university students using online survey in Mainland China. Results from exploratory factor analysis identified five smartphone addiction symptoms: disregard of harmful consequences, preoccupation, inability to control craving, productivity loss, and feeling anxious and lost, which formed the Smartphone Addiction Scale. Results show that the higher one scored in loneliness and shyness, the higher the likelihood one would be addicted to smartphone. Furthermore, this study shows the most powerful predictor inversely affecting both bonding and bridging social capital was loneliness. Moreover, this study presents clear evidence that the use of smartphones for different purposes (especially for information seeking, sociability, and utility) and the exhibition of different addiction symptoms (such as preoccupation and feeling anxious and lost) significantly impacted social capital building. The significant links between smartphone addiction and smartphone usage, loneliness, and shyness have clear implications for treatment and intervention for parents, educators, and policy makers. Suggestions for future research are discussed.
This article reports from a pilot study that was conducted in a probability-based online panel in the Netherlands. Two parallel surveys were conducted: one in the traditional questionnaire layout of the panel and the other optimized for mobile completion with new software that uses a responsive design (optimizes the layout for the device chosen). The latter questionnaire was optimized for mobile completion, and respondents could choose whether they wanted to complete the survey on their mobile phone or on a regular desktop. Results show that a substantive number of respondents (57%) used their mobile phone for survey completion. No differences were found between mobile and desktop users with regard to break offs, item nonresponse, time to complete the survey, or response effects such as length of answers to an open-ended question and the number of responses in a check-all-that-apply question. A considerable number of respondents gave permission to record their GPS coordinates, which are helpful in defining where the survey was taken. Income, household size, and household composition were found to predict mobile completion. In addition, younger respondents, who typically form a hard-to-reach group, show higher mobile completion rates.
Social media are becoming an important intermediary for interaction between governments, governments and citizens, and governmental agencies and businesses. This is due to the unique characteristics of social media: openness, participation, and sharing. However, despite rapid adoption, a growing concern and skepticism regarding the use of social media exists in the public sector. The purpose of this study is to investigate empirically the risks and benefits of social media use by public agencies. For this purpose, a research model was developed and tested in a survey of 289 government sector employees from six South Korean government research institutes. We found that both risks (i.e., social risk, time, psychological risks, and privacy concern) and benefits (i.e., social connectivity, social involvement, information attainment, and entertainment) significantly affect public sector employees’ satisfaction with and intention to use social media. However, the effect of the benefits on users’ satisfaction was stronger than the risks. The results of the study have important implications for researchers and policy makers.
People increasingly rely on social network sites (SNSs) to find out timely information about crises. Thus, emergency managers are interested in how people participate and how to promote their participation in SNSs after crises. Based on self-determination theory, this study develops a theoretical model to examine the mechanisms through which different types of motivation contribute to various participating behaviors in SNSs after crises. Survey data were collected after the Ya’an earthquake, which occurred in China on April 20, 2013. Our results show that while autonomous motivation is positively related to posting new content about the earthquake, controlled motivation is positively related to commenting on others’ content about the earthquake. Furthermore, perceived autonomy and perceived relatedness are positively related to autonomous motivation. We suggest that emergency managers may want to promote different types of motivations, depending on the specific participating behavior preferred after crises.
This study examines the relationship of social media channel utilization (activity on blogs, content communities, and social networking sites, plus posting a social media policy) by health care organizations and the brand rating of those organizations, as measured by patients who have completed the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. We found the degree of adoption of social media channels among hospitals to be 25%, which is consistent with other reports. We also found a positive relationship between social media channel utilization and patient rating of their overall hospital experience, as well as patient willingness to recommend the hospital. Based upon our findings, we introduce a social media value matrix. The matrix indicates that health care organizations utilizing a greater than average number of social media channels have significantly higher social media value scores (derived from the intersection of HCAHPS scores and social media channel prevalence) than hospitals that utilize fewer than average social media channels. Rogers’ diffusion of innovation theory is referenced to explain the rate of adoption of social media by health care organizations.
Negative publicity has an adverse effect on an organization, especially in online environments where consumers’ word of mouth travels fast. By implementing an appropriate response strategy and being attentive about consumers’ emotional reactions, an organization could minimize potential damage from crises. This explorative multiple case study decomposes each of the eight negative publicity cases into the dimensions of drug/supplement type (Lipitor and Oxyelite Pro), negative publicity source type (organizations and individuals), response execution status (response executed and no response), and defensive response type (attack the accuser and justification) in measuring consumers’ particular negative emotions (anger, anxiety, and sadness). Based on the results of the study, the following propositions are derived: (1) higher degrees of anger and sadness are correlated with the negative publicity involving a supplement; (2) a higher degree of anxiety is correlated with the negative publicity caused by individuals; (3) a higher degree of anger is correlated with the response executed; (4) response execution is the dimension that exerts the strongest impact on consumers’ negative emotions; (5) a higher degree of sadness is correlated with the late response; and (6) the degrees of anger and anxiety subside after the second response.
This article investigates unintended mobile access to surveys in online, probability-based panels. We find that spontaneous tablet usage is drastically increasing in web surveys, while smartphone usage remains low. Further, we analyze the bias of respondent profiles using smartphones and tablets compared to those using computers, on the basis of several sociodemographic characteristics. Our results indicate not only that mobile web respondents differ from PC users but also that tablet users differ from smartphone users. While tablets are used for survey completion by working (young) adults, smartphones are used merely by the young. In addition, our results indicate that mobile web respondents are more progressive and describe themselves more often as pioneers or forerunners in adopting new technology, compared to PC respondents. We further discover that respondents’ preferences for devices to complete surveys are clearly in line with unintended mobile response. Finally, we present a similar analysis on intended mobile response in an experiment where smartphone users were requested to complete a mobile survey. Based on these findings, testing on tablets is strongly recommended in online surveys. If the goal is to reach young respondents, enabling surveys via smartphones should be considered.
This study examines the relationship between individuals’ networking interests and a group’s networked structure. The data set includes 25,651 members and 12,638 mentions from Twitter-mediated communities in South Korea. Using social network and web impact analyses, we investigated the micro- and macro linkage between individuals’ interests and groups’ structure, the meso-level analysis of individual-to-individual relationships, and the hyperlinked content shared in each community. Findings suggest that different interests of individuals in joining online communities were associated with variations in those communities’ network structures: Communities with sociopolitical goals had a denser network structure and communities for interpersonal interests had a more reciprocated network. Communities for information access exhibited greater dependence on a single member, contrary to the communities for information sharing. Types of content shared in the communities also varied by interests. These findings led us to compose a network topology with visual representation, based on sociopolitical, informational, and interpersonal interests.
The literature on human-computer interaction consistently stresses the importance of reducing the cognitive effort required by users who interact with a computer in order to improve the experience and enhance usability and comprehension. Applying this perspective to web surveys, questionnaire designers are advised to strive for layouts that facilitate the response process and reduce the effort required to select an answer. In this article, we examine whether placing the answer boxes (i.e., radio buttons or check boxes) to the left or to the right of the answer options in closed questions with vertically arranged response categories enhances usability and facilitates responding. First, we discuss a set of opposing principles of how respondents may process these types of questions in web surveys, some suggesting placing the answer boxes to the left and others suggesting placing them to the right side of the answer options. Second, we report an eye-tracking experiment that examined whether web survey responding is best described by one or another of these principles, and consequently whether one of the three layouts is preferable in terms of usability: (1) answer boxes to the left of left-aligned answer options, (2) answer boxes to the right of left-aligned answer options, and (3) answer boxes to the right of right-aligned answer options. Our results indicate that the majority of respondents conform to a principle suggesting placing the answer boxes to the left of left-aligned answer options. Moreover, respondents require less cognitive effort (operationalized by response latencies, fixation times, fixation counts, and number of gaze switches between answer options and answer boxes) to select an answer in this layout.
In many cases in today’s world, sexting has replaced sexually explicit letters or messages and one time sent through the postal service. However, whereas mail traditionally involved one sender and one recipient, sexting can involve multiple parties, is a common activity for teens, and can be considered illegal. This report was an attempt to document users’ knowledge of sexting and their recognition of illegal activities. Results indicated that regardless of age or sex, individuals capable of sexting were aware of the legality and illegality of the action. However, females generally held a more narrow view of sexting in that if the sexting involved children as the victims of the sexually explicit image and not the recipient, then the action was considered illegal. Through research reports such as this one, awareness of the illegal possibilities of sexting is exposed.
The information revolution has shaped a new generation. Our study focused on the relation between the social networks that benefit from the opportunities arising from information technologies and the communication behaviors of Generation 2000 university students. According to the findings of this research, in Turkey, university students’ use of mobile Internet and social networks is increasing and becoming widespread when compared to that observed in the previous years. For both Generation 2000 and others in Turkey, Facebook is the preferred network. In contrast to the expectations, our study showed that members of Generation 2000 in Turkey do not exhibit difficulty in using electronic communication. These technologies prevent face-to-face communication, determine social networks to a certain degree, and remove the above-mentioned contradiction. We found that Generation 2000 in Turkey is aware of information technology and the possible negative effects of electronic social networks. Finally, we noted that Generation 2000 in Turkey is addicted neither to the Internet nor to electronic social networks.
In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins and King to analyze the voting intention of Twitter users in the United States (for the 2012 Presidential election) and Italy (for the two rounds of the centre-left 2012 primaries). This methodology presents two crucial advantages compared to traditionally employed alternatives: a better interpretation of the texts and more reliable aggregate results. Our analysis shows a remarkable ability of Twitter to "nowcast" as well as to forecast electoral results.
Although social media are increasingly used by employees during work, little is known about what employees are actually doing on social media or why. To remedy this key gap in the literature, a series of three studies were conducted. In Study 1, a qualitative critical incident study was conducted to develop a taxonomy of social media behaviors that are beneficial to work performance, along with a taxonomy of behaviors that are harmful. In Study 2, the Work-related Social Media Questionnaire (WSMQ) was developed to measure these behaviors. In Study 3, cross-validation and criterion-related validity evidence was collected on the WSMQ. Behaviors identified by employees as harmful to job performance were positively related to counterproductive work behaviors and negatively related to task, contextual, and adaptive job performance. Behaviors identified by employees as beneficial to job performance were generally unrelated to actual job performance. Thus, behaviors identified as harmful by employees were indeed harmful, but behaviors identified as beneficial were not beneficial. This suggests limited value in permitting access to social media by employees without a particular plan in place to utilize the features of social media productively.
Traditional consumer theory assumes that welfare is derived at the point where goods are purchased. More recent theories however argue that what matters is dependent on what happens after goods are purchased. Such information requires surveys that are specifically designed for the purpose. Accordingly, Internet use data are few and far between in developing countries. Recently, however, such data have become available for II African countries and my intention in this article is to use them to assess welfare more realistically across the countries in question. Among the questions asked are do the patterns of use favor one set of countries over others or are the observations more random in character? Which use mechanisms are most important across the sample and why? How do these results compare with those of a developed country such as the United States?
Interaction facilitated by social media is becoming an integral part of life in contemporary society, tweaking the human psyche's deep need to connect. Having changed the creation, sharing, and consumption of information, it must be inevitably integrated into the operation of most human organizations. While some organizations readily adapt themselves to social media, the majority have struggled. This special issue of the Social Science Computer Review investigates different aspects of social media use in government, nonprofit, education, and health care organizations.
Universities have every reason to avoid damaging their reputations through mismanaged crises. Moreover, universities have the moral duty to protect their students from harm by effective communication in a time of crisis. Social media have evolved into the fastest and most direct means to communicate with student populations. In this study, we experimentally tested the use of Twitter and Facebook as crisis communication media at a university. We further observed the effects of the communication source (university or dean) and the crisis information (instructing or adapting) on secondary communication by the students (e.g., sharing the message and leaving a reaction). The role of the dean as an information source seemed to incite action by students. We also found some counterintuitive effects, particularly with regard to the type of crisis information communicated on Facebook or Twitter, by the dean or the university.
Experience sampling or ecological momentary assessment offers unique insights into how people think, feel, and behave in their natural environments. Because the method is able to capture situational variation as it happens in "real time," experience sampling has become an increasingly popular method in social and personality, psychology, and beyond. With the ubiquity of smartphone ownership and the recent technical advances, conducting experience sampling studies on participants’ own devices has become increasingly easy to do. Here, we present one reliable, user-friendly, highly customizable, and cost-effective solution. The web-based application, SurveySignal, integrates the idea of using short message service (SMS) messages as signals and reminders, according to fixed or random schedules and of linking these signals to mobile surveys designed with common online survey software. We describe the method and customizable parameters and then present evaluation results from nine social–psychological studies conducted with SurveySignal (overall N = 1,852). Mean response rates averaged 77% and the median response delay to signals was 8 min. An experimental manipulation of the reminder signal in one study showed that installing a reminder SMS led to a 10% increase in response rates. Next to advantages and limitations of the SMS approach, we discuss how ecologically valid research methods such as smartphone experience sampling can enrich psychological research.
The present study conducts cross comparisons among nonprofits’ leading Internet platforms regarding use of dialogic principles and investigates relationships between this use and financial capacity. A content analysis was conducted of three Internet platforms (website, Facebook, and Twitter) of 60 U.S.-based environmental nonprofit organizations. The results reveal that (1) 85% of the organizations use either Facebook or Twitter, (2) the overall extent of dialogic principle employment is the highest for the website, followed by Facebook and Twitter, (3) positive correlations are found only between the website and Twitter in the dialogic principles of the dialogic loop and the usefulness of information to the public, and (4) organizational financial capacity is positively correlated only with Twitter in the overall dialogic principle employment. The results indicate that, although nonprofits operate multiple Internet platforms for relation building with the public, they substantially rely on their websites and use Facebook and Twitter to supplement particular dialogic features that are limited on websites.
Many public organizations are opening their data to the general public and embracing social media in order to stimulate innovation. These developments have resulted in the rise of new, infomediary business models, positioned between open data providers and users. Yet the variation among types of infomediary business models is little understood. The aim of this article is to contribute to the understanding of the diversity of existing infomediary business models that are driven by open data and social media. Cases presenting different modes of open data utilization in the Netherlands are investigated and compared. Six types of business models are identified: single-purpose apps, interactive apps, information aggregators, comparison models, open data repositories, and service platforms. The investigated cases differ in their levels of access to raw data and in how much they stimulate dialogue between different stakeholders involved in open data publication and use. Apps often are easy to use and provide predefined views on data, whereas service platforms provide comprehensive functionality but are more difficult to use. In the various business models, social media is sometimes used for rating and discussion purposes, but it is rarely used for stimulating dialogue or as input to policy making. Hybrid business models were identified in which both public and private organizations contribute to value creation. Distinguishing between different types of open data users was found to be critical in explaining different business models.
This article describes an agent-based simulation model of ethnonationalist radicalization between political actors and their constituencies based upon evidence from the former Yugoslavia. The central mechanism is the recursive feedback between political and cultural dynamics, focusing on processes prior to the outbreak of actual violence. The results offer theoretical insights by revealing mechanisms that lead to escalation. These can be found within politics as well as among the population: between conflicting ethnically homogeneous regions, opposing radicalization forces fuel an escalation spiral. These processes are driven by political influences. Challenging the theory that diversity breeds conflict, this suggests that multiethnic regions are more capable of withstanding political pressures. However, they are vulnerable to imported violence, driven by the local population. This finding is tested with a different model of the same events, in which different implemented mechanisms generate results, in line with the diversity-breeds-conflict theory. A comparative discussion demonstrates how simulation is sensitive to theoretical predispositions.
Results of the present survey (n = 888) suggest that having strong social ties (or bonding social capital) fosters generalized trust, in support of conflict theory. There was no link between bridging social capital, or one’s more diverse ties, and trust. Facebook use was found to have an indirect but positive influence on trust through levels of bonding social capital. Civic engagement was also positively related to trust through the same measure of bonding social capital, allowing like-minded members of civic groups to connect, which spilled over to trust. Neither Facebook use nor civic engagement directly influenced generalized trust. This study suggests the viability of both physical (civic) and digital (Facebook) modes of reengaging trust in an ever-diversifying society. The "virtuous circle," in which social trust and civic engagement prop one another up in a reciprocal fashion, instead looks like a figure eight here. Each measure indirectly boosted the other by first growing bonding social capital. When considered alongside divergent findings from Canada, this appears to be an American response to the increasing size of racial minority groups. Hispanic citizens make up the same portion of the American population as do all minority groups in Canada combined. These findings then represent a White reaction to an increasing Hispanic presence in America. Bounded solidarity in the form of strong, homogenous ties is shown as the path to trust in this setting.
This work introduces a multiagent model for informal communication about cheating merchants among investing Genoese traders in the 12th century. The model builds on previous, game theory focused work of Avner Greif and extends it by enabling communication between Genoese traders. A trust-based cooperation model is tested across different network topologies as well as two different communication modes: (a) a reactive one representing Genoese trader interrelations and (b) a more proactive one that is based on accounts on the relationships among a North African traders collective, known as the medieval Maghribi Traders. The simulation shows that even for high levels of initial trust among Genoese, their mode of communication would not have sufficed to collectively identify cheating merchants and prevent them from future transactions. The results obtained from the tested network topologies are further discussed in the light of literature accounts of both historical societies.
The theory of constructuralism describes how shared knowledge, representative of cultural forms, develops between individuals through social interaction. Constructuralism argues that through interaction and individual learning, the social network (who interacts with whom) and the knowledge network (who knows what) coevolve. In the present work, we extend the theory of constructuralism and implement this extension in an agent-based model (ABM). Our work focuses on the theory’s inability to describe how people form and utilize stereotypes of higher order social structures, in particular observable social groups and society as a whole. In our ABM, we formalize this theoretical extension by creating agents that construct, adapt, and utilize social stereotypes of individuals, social groups, and society. We then use this model to carry out a virtual experiment that explores how ethnocentric stereotypes and the underlying distribution of culture in an artificial society interact to produce varying levels of social relationships across social groups. In general, we find that neither stereotypes nor the form of underlying cultural structures alone are sufficient to explain the extent of social relationships across social groups. Rather, we provide evidence that shared culture, social relations, and group stereotypes all intermingle to produce macrosocial structure.
Punishment plays a crucial role in favoring and maintaining social order. Recent studies emphasize the effect of the norm-signaling function of punishment. However, very little attention has been paid so far to the potential of group punishment. We claim that when inflicted by an entire group, the recipient of punishment views it as expressing norms. The experiments performed in this work provide evidence that humans are motivated not only by material incentives that punishment imposes but also by normative information that it conveys. The same material incentive has a different effect on the individuals’ future compliance depending on the way it is implemented, having a stronger effect when it also conveys normative information. We put forward the hypothesis that by inflicting equal material incentives, group punishment is more effective in enhancing compliance than uncoordinated punishment, because it takes advantage of the norm-signaling function of punishment. In support of our hypothesis, we present cross-methodological data, that is, data obtained through agent-based simulation and laboratory experiments with human subjects. The combination of these two methods allows us to provide an explanation for the proximate mechanisms generating the cooperative behavior observed in the laboratory experiment.
This article describes the design and operation of an agent-based model that represents aspects of hunter-gatherer subsistence, technology, and cultural identity. The agents (representing families or households) in the model interact in a world that has a seasonally variable resource density. Agents must collect resources every step, either independently (by "gathering") or with cooperation from neighboring agents ("hunting"). Several parameters affect cooperation: understanding these effects is one of the main focus of this article. Another focus is understanding the effects of cooperation in terms of cultural diversity/homogeneity. Some input parameters are historically and ethnographically calibrated, and the results are contrasted, with ongoing archaeological research of Patagonian hunter-gatherers (from 7000 BC or even earlier to 19th century). Specific research questions include how do processes of convergence and divergence occur between groups of hunter-gatherers over the long term? How could the autonomous local interactions of heterogeneous bounded rational agents generate this kind of regularity? What role outside influence plays on the formation of ethnic identities? Our aim is to integrate the state-of-the-art knowledge from different social sciences and technological developments into a fruitful approach to develop sociohistorical studies
This study extends selectorate theory in the form of an agent-based model to explore how the leader’s ethnic policy—ethnic exclusion or inclusion—influences the risk of rebellion and leader survival in different sizes of the minimum winning coalition. The theoretical simulation shows that when the minimum winning coalition is small, (1) highly exclusive leaders not only survive longer in power but also face a lower risk of violent removal from office than moderately exclusive leaders; (2) leaders who pursue an inclusive ethnic policy are more likely to be overthrown by disaffected members of the ruling coalition; and (3) there is an inverted U-shaped relationship between the level of ethnic exclusion and the risk of rebellion, with the greatest risk of rebellion among semiexclusive regimes. These findings indicate that an exclusive ethnic policy provides political benefits to nondemocratic leaders even if it motivates excluded groups to rebel.
Social networks characterize the set of relationships among a population of social agents. As such, their structure both constrains and is constrained by social processes such as partnership formation and the spread of information, opinions, and behavior. Models of these coevolutionary network dynamics exist, but they are generally limited to specific interaction types such as games on networks or opinion dynamics. Here we present a dynamic model of social network formation and maintenance that exhibits the characteristic features of real-world social networks such as community structure, high clustering, positive degree assortativity, and short characteristic path length. Although these macrostructural network properties are stable, the network microstructure undergoes continuous change at the level of relationships between individuals. Notably, the edges are weighted, allowing for gradual change in relationship strength in contrast to more abrupt mechanisms, such as rewiring, used in other models. We show how the structural features that characterize social networks can arise as the result of constraints placed on the interactions between individuals. Here we explore the relationship between structural properties and four idealized constraints placed on social interactions: space, affinity, time, and history. We show that spatial embedding and the subsequent constraints on possible interactions are crucial in this model for the emergence of the structures characterizing social networks.
This article provides an overview of the social simulation approach to the study of social phenomena. We focus especially on the relevance of heterogeneity of social behavior and dynamics and the complex interplay of agent behavior and social structure. The article identifies the peculiarities and the explanatory achievements of this approach and then discusses its prospects and challenges. Special attention is given to (i) how micro-level behavioral detail can be used to understand social patterns and dynamics; (ii) the importance of the meso level of social networks; and (iii) the two-way, process linkages between micro and macro aspects as a fundamental source of social uncertainty and unpredictability.
Across the world, youth are embracing the concepts of freedom of speech, right to opinion, and modern information technology in all its aspects and are trying to find use for it. The Arab Spring revolutions that began in 2011 and which are still ablaze reflect this fact. Lebanon is the most democratic country in the Middle East and North Africa region. The youth of Lebanon are adept users of web-based communication tools but are they eager to use this technology to connect with their political leaders? The results of this study show significant interest of youth in electronic-based communication with politicians. However, this interest may not be translated into material voting at the polls.
This study sought to investigate whether Internet addiction (IA) is associated with age, gender, BIG-5 personality, and chronotype in a Turkish university student sample. Six hundred and sixteen students filled out a set of questionnaires. We here report—to our knowledge for the first time—an association between IA and chronotype. Evening types and males had higher IA scores than others. Furthermore, agreeable and conscientious students reported lower IA. No consistent relationship was observed between students’ IA scores and openness to experience, extraversion, and neuroticism. We conclude that evening types may be more prone to IA than morning-oriented persons because eveningness is related to personality styles that foster Internet addiction.
A computer simulation based on both game theory and the cellular automaton model was conducted to investigate the effects of individuals’ interactions and certain conditions on the spread of rule-breaking behavior in public places. Four decision matrices representing obedient, deviant, conforming, and contrary principles were prepared experimentally. The ratio of these principles ranged from 1:2:3:4 to 4:3:2:1 (obedient:deviant:conforming:contrary). There were a total of 24 data sets with each data set composed of 10 decision matrices. In addition to these 24 data sets, the ratio 1:1:1:1 was prepared. This data set was composed of four decision matrices. The results indicated that rule-breaking behavior spreads under the following conditions: (A) when people act according to both individual factors (e.g., their attitudes) and situational factors (e.g., their neighbors’ behavior); (B) when there are more deviant people than obedient people; (C) when the intensity of rule-breaking behavior is higher than that of rule-obeying behavior. Condition A is an important factor. If conditions B or C are satisfied, the spread of rule-breaking behavior does not occur necessarily. At a certain probability threshold, rule-breaking behavior spreads sharply when people act based on individual factors (e.g., their attitudes); the spread of such behavior cannot be attributed solely to situational factors (e.g., neighbors' behavior). There is only a fine line between rule breaking and obeying near the probability threshold.
This study investigated the role of desire thinking in predicting problematic Internet use (PIU) independently of weekly Internet use, anxiety, depression, and craving for Internet use. A sample of 250 Internet users completed the following self-report instruments: Hospital Anxiety and Depression Scale, Internet Use Craving Scale, Desire Thinking Questionnaire, and Internet Addiction Test. The sample was then divided into two subgroups: problematic Internet users (n = 90) and nonproblematic Internet users (n = 140). Mann–Whitney U tests revealed that all variable scores were significantly higher for problematic Internet users than nonproblematic Internet users. A logistic regression analysis indicated that imaginal prefiguration was a predictor of classification as problematic Internet user over and above weekly Internet use, anxiety, depression, and craving for Internet use. A hierarchical regression analysis, on the combined sample, indicated that both verbal perseveration and imaginal prefiguration predicted PIU independently of weekly Internet use, anxiety, depression, and craving for Internet use. These results add to the argument that the construct of desire thinking is relevant in understanding of addictive behaviors including PIU.
Understanding virtual community (hereinafter as VC) participation is of importance to VC organizers as well as VC researchers. Although VC participation has been explored from diverse perspectives, few studies can offer a comprehensive theoretical framework to explain why people participate in VCs. This article contributes to VC research by proposing and empirically validating an exploratory theoretical framework from the interpersonal relationship perspective using two interpersonal relationship theories—the Triandis interpersonal behavior model from social psychological angle and fundamental interpersonal relationship orientation from communicational angle to explain two types of VC participation—behavior to obtain information and behavior to give information. Data were collected in three representative VCs. Data analysis results showed that the two interpersonal relationship theories are effective in explaining VC participation. This article contributes to the existing body of knowledge on VCs by providing an integrative interpersonal relationship framework to explain VC participation, that is, members participate in VCs to satisfy their interpersonal relationship needs at three levels—inclusion, control, and affect through the dynamic interpersonal process expressed as covert to overt psychological process.
Some recent studies have illustrated a positive relationship between social media use and political participation among young people. Researchers, however, have operationalized social media usage differently. This article adopts a multidimensional approach to the study of the impact of social media. Focusing on Facebook (FB), the most widely utilized social networking site in Hong Kong, this study examines how time spent on FB, exposure to shared political information, network size, network structural heterogeneity, and direct connection with public political actors relate to young people’s online and offline political participation. Analysis of a survey of university students (N = 774) shows that participation is explained most prominently by direct connection with public political actors, followed by exposure to shared political information. These two variables also mediate the impact of other dimensions of FB use on political participation.
Online self-presentation strategies are critical for female candidates to develop and deliver effectively. This is because the media appear to cover male and female candidates differently in news coverage, and research-based evidence continues to suggest that voters hold male and female candidates to different standards in mixed-gender races. This study examines how women running in mixed-gender races during the 2012 general election cycle employed self-presentation strategies to present a viable image for election. Candidate websites from U.S. House races featuring a female and male candidate are analyzed for their overall use of feminine versus masculine styles, as well as style-based issue discussion and image presentation. The results are compared to past research to further highlight relevant changes over time as women continue to construct their candidacies and define their space—and voice—within the political environment.
This research examined the influence of attention to specific forms of traditional and online media on young adults’ online and offline political participation as well as voter turnout during the fall 2012 presidential campaign. A three-wave panel survey demonstrated that attention to traditional media did not increase offline and online political participation in September; instead, participation was heightened by attention to online sources, particularly presidential candidate websites, Facebook, Twitter, and blogs. In the following months, individual-level change in participation was attributable to attention to several online media sources as well as change in media attention. In the case of voter turnout, results suggest that television attention was positively linked to voter likelihood in September but was negatively linked to individual-level change in voter turnout in November.
Twitter has been lauded for its potential political value by academics, journalists, and politicians; yet, we know little about the citizenry’s use of Twitter to engage in politics. Under the backdrop of the 2011 gubernatorial elections, we observed Twitter users’ direct engagement in the electoral process by collecting usernames and tweets of anyone who mentioned a candidate. After the elections were called, we employed an original survey via Twitter of these political tweeters to answer the question, who tweets about politics? Unsurprisingly, the results of our logit analysis demonstrate that strong partisans and those exhibiting high levels of traditional political participation activity tweet about politics most often which supports those who argue that we can expect to find the same political activists online as offline. However, we also find evidence that racial minorities and secularists are engaged in the electoral conversation on Twitter suggesting that some marginalized groups may have found a political outlet.
This study analyzes whether greater levels of Internet access closed the participation gap between individuals of lower and higher socioeconomic status (SES) in the early stages of the 2012 presidential campaign. Our analysis of data from the Pew Research Center demonstrates that greater levels of access to the Internet are significantly associated with greater political knowledge and engagement for low SES individuals, but not high SES individuals. We explain our results in the context of incidental learning among the disengaged public during high-profile political events, such as a presidential election.
By being embedded in everyday life, social networking sites (SNSs) have altered the way campaign politics are understood and engaged with by politicians and citizens alike. However, the actual content of social media has remained a vast but somewhat amorphous and understudied entity. The study reported here examines public sentiment as it was expressed in just over 1.42 million social media units on Facebook and Twitter to provide broad insights into dominant topics and themes that were prevalent in the 2012 U.S. election campaign online. Key findings include the fact that contrary to what one might expect, neither presidential candidate was framed in an overly critical manner in his opponent’s Facebook space nor on Twitter’s dedicated nonpartisan election page. Beyond this, similarities and divergences in sentiment across social media spaces are observed that allow for a better understanding of what is being communicated in political social media.
Twitter offers a function called live-tweeting that allows users to communicate about events with each other in real time. This study examines the use of live-tweeting during a 2012 Republican Primary Debate by examining the 181,780 tweets posted during the nationally televised debate. Live-tweeting offers users an opportunity to engage in public conversation about political events and thus potentially influence the framing of what occurred. Our study examines whether citizens utilize the opportunity to contribute to the political narrative or if elite users dominate political conversations through an analysis of tweets used by both groups. Findings show that there were very few differences between the elite and nonelite social media conversations and that elite users views were spread farther than nonelite views.
The increasing popularity of social network sites (SNSs) in election campaigns provides a unique climate for scholarly inquiry. The study reported here builds upon Zhang, Johnson, Seltzer, and Bichard and investigates the impact of different types of SNS use on voters’ attitudes and behavior during the 2012 U.S. presidential campaign. Sites such as Facebook, Google Plus, Twitter, and YouTube are included to offer a robust assessment of distinct relationships. A national online panel of Internet users was utilized to examine reliance on SNSs and the multiple consequences on political attitudes and behavior such as political participation, political interest, selective exposure, selective avoidance, and strength of party affiliation. The findings are evaluated for theoretical and practical implications on democratic governance.
A posttest-only experimental design is used to test the effects of humorous negative video ads from the 2012 presidential campaign on evaluations of Barack Obama and Mitt Romney among young people. Findings show that ads targeting Romney had a negative effect on attitudes toward him. Romney also had his evaluations lowered as the result of respondents viewing third-party ads attacking Obama. This may be consistent with some research that suggests that negative political ads have a "backlash," or "boomerang" effect on their source. Obama, on the other hand, was largely insulated from both target and source effects. The study suggests first that candidates who decide to "go negative" may not be able to insulate themselves from unintended negative effects by framing their ads in a humorous fashion. Moreover, because the anti-Obama ads were sponsored by a third party, it suggests that the source really might matter in terms of the effects ads have on "their" candidates.
Diffusion of innovation theory is used to explain adoption of Facebook in the 2012 campaigns for the U.S. Congress and to identify characteristics that differentiate the small subset of candidates who did not create a Facebook presence from the large majority who did. Models of Facebook adoption for House candidates reveal that there are no differences between Republicans and Democrats. Nonadopters are significantly more likely to be challengers or open-seat candidates, poorly financed candidates, candidates in noncompetitive races, and older. Among nonincumbents, Republicans, and candidates from Republican-oriented districts are more likely to adopt. This study serves as one of the first examinations of social media adoption by congressional candidates in the 2012 elections and discusses relevant developments and trends in adoption since Facebook’s introduction in 2006.
This study tested the reproduction hypothesis that the Internet produces positive payoffs for those in privileged social positions, while disfavoring marginalized communities. Using a national sample of adult Internet users (n = 419), the first premise of this study investigated the impacts of (1) sociodemographic status, (2) Internet access indicators, and (3) their interactions on the variations of capabilities, as assessed through discrete measures of Internet-related personal information skill and knowledge. The second premise introduced the factor of individual motivation in interaction with sociodemographics and Internet access indicators. Hierarchical logistic regressions showed manifest age and gender disparities, with the significant interactions indicating that Internet access exacerbates existing offline status disparities. The reinforcement of digital divide was particularly salient in knowledge dimensions. The findings are discussed with regard to the conditions that incubate systematic differences in people’s ability to understand or resist data surveillance. Implications for policy initiatives are offered.
The considerable growth in the number of smart mobile devices with a fast Internet connection provides new challenges for survey researchers. In this article, I compare the data quality between two survey modes: self-administered web surveys conducted via personal computer and those conducted via mobile phones. Data quality is compared based on five indicators: (a) completion rates, (b) response order effects, (c) social desirability, (d) non-substantive responses, and (e) length of open answers. I hypothesized that mobile web surveys would result in lower completion rates, stronger response order effects, and less elaborate answers to open-ended questions. No difference was expected in the level of reporting in sensitive items and in the rate of non-substantive responses. To test the assumptions, an experiment with two survey modes was conducted using a volunteer online access panel in Russia. As expected, mobile web was associated with a lower completion rate, shorter length of open answers, and similar level of socially undesirable and non-substantive responses. However, no stronger primacy effects in mobile web survey mode were found.
In this study, we explore to what extent the visual presentation of open-ended probes, in connection with different prior probing exposure, impacts on response quality. We experiment with two text box sizes for a specific immigrant probe (Which type of immigrants were you thinking of when you answered the question?). On the one hand, we use a standard size equal to the other text box sizes in the survey but oversized for the specific response task. On the other hand, we use a smaller text box which fits the response task. The other probes in the survey that use the standard text box are mainly category-selection probes that ask for a reasoning for the chosen answer value. Due to randomized rotation of questions, respondents receive different numbers of category-selection probes prior to the immigrant probe, resulting in different degrees of exposure to category-selection probing prior to the immigrant probe. For the immigrant probe, we find that respondents who receive the standard text box and who have had a high exposure to category-selection probing are more likely to provide mismatching answers: The mismatch consists of not answering the specific immigrant probe but rather providing a reasoning answer as typically expected for a category-selection probe. Thus, previous experience with probing in the questionnaire can override the actual probe wording. This problem can be minimized by considering possible carryover effects of prior probes and using an appropriate survey design strategy.
Use of optimization models in science and policy applications is often problematic because the best available models are very inaccurate representations of the originating problems. Such is the case with electoral districting models, for which there exist no generally accepted measures of compactness, in spite of many proposals and much analytical study. This article reports on an experimental investigation of subjective judgments of compactness for electoral districts. The experiment draws on a unique database of 116 distinct, legally valid districting plans for the Philadelphia City Council, discovered with evolutionary computation. Subjects in the experiment displayed, in the aggregate, remarkable agreement with several standard measures of compactness, thus providing warrant for use of these measures that has heretofore been unavailable. The exercise also lends support to the underlying methodology on display here, which proposes to use models based on subjective judgments in combination with algorithms that find multiple solutions in order to support application of optimization models in contexts in which they are only very approximate representations.
The advent of the Internet has opened wholly new possibilities for data collecting. At the same time, several unanswered methodological pitfalls are present, possibly questioning the usability of data from web surveys. This article contributes to the scientific debate regarding the usability and reliability of web surveys in the social sciences by discussing the reliability of the data collected in passive sampling web surveys. The article analyzes two surveys containing the same questions, of which the first is based on a probabilistic offline sample, the other on a passive sampling online sample. Both surveys were aimed at measuring the respondents’ knowledge of politics. The findings related to the demographic characteristics were in-line with previous research: men, young, better educated, and politically interested persons dominated the online sample. Regarding the reliability of the results of the knowledge questions, the findings show that online surveys are capable of providing valuable and reliable information about the differences (and similarities) between different groups of respondents, that is, about general trends. However, the findings strongly suggest that passive sampling web surveys should not be used for drawing conclusions about the absolute levels of political knowledge in a population. The big question which remains is whether the Internet can be seen as just another sampling environment or does the "unstructured anonymity" of the Internet require tapping into a wholly new sampling methodology.
SaTScan was developed by Martin Kulldorff to scan for temporal, spatial, and spatial temporal clusters. It places circles or ellipses of continuously varying size over a spatial study area and can add time as a continuously varying third-dimension scan. The program offers a wide variety of scanning models. Paraphrasing Kulldorff, SaTScan calculates a Poisson-based model according to a known population at risk, a Bernoulli model which allows for cases and controls, a space-time permutation model that needs only case data, an ordinal model, an exponential model for survival analysis, and a normal model for continuous data. Either the data may be aggregated to a geographic region or each case may have unique coordinates. The end result is quite intuitive and includes the location of a cluster in space and time and the significance of the cluster based on a Monte Carlo simulation. Although analysis is easy to do and interpret, input and output are unnecessarily cumbersome. SaTScan has no direct interface with any statistical, database, or GIS program, but it requires their use.