Social Sciences identify similarity and mutual trust as main criteria to consider in group formation processes. On this basis, we present a group formation technique which exploits measures of both similarity and trust, in order to improve the compactness of groups in Online Social Networks. Similarity and trust have been jointly exploited to design two algorithms designed to match groups and users, in order to capture the gain of a user who desires to join with a group and the benefit of the group itself. Experimental results show that trust is more valuable than similarity in forming groups and that the two proposed algorithms are capable to deal with large networks.
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