Triads, Transitivity, and Social Effects in User Interactions on Facebook

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Most computational techniques that analyze Online Social Networks (OSNs) aim to discover patterns in a network's structure and the behavior of its users, but do not seek to understand how people's motives lead to these patterns. Studying the social effects that cause these patterns, however, can produce deeper insights that may transcend a specific network and are generically applicable. Therefore, a more promising approach is to anchor computational techniques to the underlying social effects that can explain the reasons behind why users interact the way they do. In this paper, we discover how the social effects of stature, relationship strength, and egocentricity shape the interactions among Facebook users. These effects are explored through transitivity in triads, which are network units that capture dynamics among triples of users. The analysis suggests that Facebook interactions are influenced by users with concentrated stature and strong bonds. However, the activities of popular and over-active users have little influence.


Presented at the Fifth International Conference on Computational Aspects of Social Networks, Fargo, ND, August 12-14, 2013.



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