Assortative Mixing in Activity-based Online Social Networks

Prior research has demonstrated that social influences can affect collective health outcomes, however, research on social dynamics in the context of such behaviors, for example exercise or eating habits, is still in its infancy. Here, we use data from the platform Strava, an online social network designed to promote increased activity and fitness as a result of peer to peer interaction, digital badges, and data-driven engagement, to explore differences in personal network structure among users. In particular we investigate activity-based assortative mixing, describing the extent to which specific groups (e.g., gender or country of residence) of users show homophilous social ties. Our results have important implications to the work on social influence mechanisms and network-based interventions which utilize network processes to promote or contain certain behaviors or actions in a population.