Efficient unveiling of multi-members in a social network
With the rapid growth of the Web 2.0, the discovery of key actors in social networks, called influencers, mediators, ambassadors or experts, has recently received a renewed of attention. In this article, we consider a particular type of actor that we call a multi-member since he belongs to several communities. We introduce a methodological framework to identify these actors in a hypergraph, in which the vertices are the actors and the hyperedges are the communities. We also show that detecting such multi-members is similar to the problem of the determination of a subset of minimal transversals of a hypergraph. An efficient algorithm that relies on the connection between the definition of a multi-member and that of an essential itemset is also introduced. Experiments done on several datasets showed that the introduced algorithm outperforms the pioneering ones of the literature.
social network hypergraph minimal transversal essential itemset