Non-existence of stable social groups in information-driven networks

Description

We study a group-formation game on an undirected complete graph G with all edge-weights in a set W ⊆ R ∪ {−∞}. This work is motivated by a recent information-sharing model for social networks (Kleinberg and Ligett, GEB, 2013). Specifically, we consider partitions of the vertex-set of G into groups. The individual utility of any vertex v is the sum of the weights on the edges uv between v and the other vertices u in her group.-Informally, u and v represent social users, and the weight of uv quantifies the extent to which u and v (dis)agree on some fixed topic.-For a fixed integer k ≥ 1, a k-stable partition is a partition in which no coalition of at most k vertices would increase their respective utilities by leaving their groups to join or create another common group. Before our work, it was known that such a partition always exists if k = 1 (Burani and Zwicker, Math. Soc. Sci., 2003). We focus on the regime k ≥ 2.• Our first result is that when all the social users are either friends, enemies or indifferent to each other (i.e., W = {−∞, 0, 1}), a partition as above always exists if k ≤ 2, but it may not exist if k ≥ 3. This is in sharp contrast with (Kleinberg and Ligett, GEB, 2013) who proved that k-stable partitions always exist, for any k, if W = {−∞, 1}.• We further study the intriguing relationship between the existence of k-stable partitions and the allowed set of edge-weights W. Specifically, we give sufficient conditions for the existence or the non existence of such partitions based on tools from Graph Theory. Doing so, we obtain for most sets W the largest k(W) such that all graphs with edge-weights in W admit a k(W)-stable partition.• From the computational point of view, we prove that for any W containing −∞, the problem of deciding whether a k-stable partition exists is NP-complete for any k > k(W).Our work hints that the emergence of stable communities in a social network requires a trade-off between the level of collusion between social users, and the diversity of their opinions.

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