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Measuring the balance of signed networks and its application to sign prediction

2017; Institute of Physics; Volume: 2017; Issue: 6 Linguagem: Inglês

10.1088/1742-5468/aa73ef

1742-5468

Ranveer Singh, Bibhas Adhikari,

Peer-to-Peer Network Technologies

We propose a parametrized walk-based measure for the lack of balance in signed networks inspired by the Katz measure of similarity of two vertices in a network. We show that the performance of the proposed measure is marginally better than a recently proposed walk-based measure of the lack of balance for an undirected version of the real-world signed networks: Epinions, Slashdot and WikiElection. The proposed measure can be used to distinguish signed social networks on the basis of their degree of lack of balance. We also establish that cycles of shorter lengths can predict the sign of an edge in these signed networks better than the longer cycles by using the Katz prediction rule.