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Connecting Theory to Social Technology Platforms: A Framework for Measuring Influence in Context

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American Behavioral Scientist

Published online on

Abstract

In this article, the authors synthesize 3 years of social technologies research, including studies of Facebook, Twitter, and GitHub, to present a theory driven framework to guide future social scientific research using "Big Data." They connect levels of analysis derived from empirical study of influence to the electronic trace data generated by social technologies. Specifically, the authors outline a relationship between social media technology platforms, individual goals for participation, and emergent small groups to inform future research on influence in social technologies. They incorporate theory from small group literature, communities and networks of practice, and media theory to explicate a contextual framework for measuring influence. In their discussion, the authors build on the contrast between influence indicators in Facebook, Twitter, and GitHub to argue for a greater focus on the influence abstractions of articulation and affiliation.