Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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In this paper we study the community structure of endorsement networks, i.e., social networks in which a directed edge u → v is asserting an action of support from user u to user v. Examples include scenarios in which a user u is favoring a photo, liking a post, or following the microblog of user v. Starting from the hypothesis that the footprint of a community in an endorsement network is a bipartite directed clique from a set of followers to a set of leaders, we apply frequent itemset mining techniques to discover such bicliques. Our analysis of real networks discovers that an interesting phenomenon is taking place: the leaders of a community are endorsing each other forming a very dense nucleus.