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Understanding the forces governing human behavior and social dynamics is achallenging problem. Individuals' decisions and actions are affected byinterlaced factors, such as physical location, homophily, and social ties. Inthis paper, we propose to examine the role that distinct communities, linked tothese factors, play as sources of social influence. The ego network istypically used in the social influence analysis. Our hypothesis is thatindividuals are embedded in communities not only related to their direct socialrelationships, but that involve different and complex forces. We analyzephysical, homophily, and social communities to evaluate their relation withsubjects' behavior. We prove that social influence is correlated with thesecommunities, and each one of them is (differently) significant for individuals.We define community-based features, which reflect the subject involvement inthese groups, and we use them with a supervised learning algorithm to predictsubject participation in social events. Results indicate that both communitiesand ego network are relevant sources of social influence, confirming that theego network alone is not sufficient to explain this phenomenon. Moreover, weclassify users according to the degree of social influence they experiencedwith respect to their groups, recognizing classes of behavioral phenotypes. Toour knowledge, this is the first work that proves the existence of phenotypesrelated to the social influence phenomenon.

On the Social Influence in Human Behavior: Physical, Homophily, and Social Communities