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Predicting Positive and Negative Links in Online Social Networks. Jure Leskovec Stanford university, Daniel Huttenlocher , Jon Kleinberg Cornell University www 2010 20100709 Presented by Seong yun Lee. Outline. Introduction Dataset Description Predicting Edge Sign
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Predicting Positive and Negative Links in Online Social Networks
Jure Leskovec
Stanford university,
Daniel Huttenlocher, Jon Kleinberg
Cornell University
www2010
20100709
Presented by Seongyun Lee
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Let G be a signed, undirectedcomplete graph in which each triangle has an odd number of positive edges. Then the nodes of G can be partitioned into two sets A and B (where one of A or B may be empty), such that all edges within A and B are positive, and all edges with one end in A and the other in B are negative.
Let G be a signed, directed tournament, and suppose that all sets of three nodes in G are statusconsistent. Then it possible to order the nodes of G as v1, v2, . . . , vn in such a way that each positive edge (vi, vj) satisfies i < j, and each negative edge (vi, vj ) satisfies i > j.