Community-centric analysis of user engagement in Skype social network

Traditional approaches to user engagement analysis focus on individual users. In this paper we address user engagement analysis at the level of groups of users (social communities). From the entire Skype social network we extract communities by means of representative community detection methods each one providing node partitions having their own peculiarities. We then examine user engagement in the extracted communities putting into evidence clear relations between topological and geographic features of communities and their mean user engagement. In particular we show that user engagement can be to a great extent predicted from such features. Moreover, from the analysis it clearly emerges that the choice of community definition and granularity deeply affect the predictive performance.