Tick populations and tick‐borne diseases like Lyme borreliosis have been steadily increasing since the mid‐1990s. Realizing the threat that ticks pose to public health, two Dutch citizen science projects have collected tick bite reports since 2006. This unique volunteered geographical dataset, which currently has nearly 35,000 reports, was used to identify environmental and other circumstantial factors associated with tick bites. For this, we first enriched the tick bite reports with temperature, precipitation, vegetation and volunteered data associated with the location of the tick bite. Using this enriched dataset, we then derived a series of features to characterize the environmental and volunteer‐related conditions in which each tick bite occurred. Next, we discretized these features using the Jenks Natural Breaks algorithm and, after that, we mined frequent environmental patterns associated with tick bites using the AprioriClose algorithm. Finally, we checked that these patterns are specifically associated with the tick bites by comparing them with the frequent patterns mined from pseudo‐random locations. The frequent patterns were visualized using heat maps and ring maps and two representative patterns associated with tick bites were projected into geographic space to study their spatio‐temporal distribution. Our results show that factors linked to human activity are more relevant to model tick bites than seasonal accumulations of temperature, vegetation or precipitation. In particular, the number of warm and dry days per season are present in a significant number of patterns and the majority of tick bites are produced within a distance of half a kilometer of a forest, recreational or built‐up area. The study of patterns in the time‐series revealed that there are several persistent patterns consistently occurring each year and the validation process showed that the volunteer tick bites collection is capturing environmental conditions associated with tick bites, suggesting that these reports have a high scientific value. These results support the creation of a Dutch tick bite risk map that, in turn, will open the door to the design of public health interventions to reduce the incidence of Lyme disease.