Role of Weak Ties in Link Prediction of Complex Networks

Details Role of Weak Ties in Link Prediction of Complex Networks Role of Weak Ties in Link Prediction of Complex Networks

2009-07-10

arxiv.org/abs/0907.1728v2

Computer Science

Information Retrieval

4 pages, 1 figure and 2 tables. Accepted by CIKM workshop, see http://www.dcs.bbk.ac.uk/~dell/cnikm09/#programme

Scientific paper

Plenty of algorithms for link prediction have been proposed and were applied to various real networks. Among these works, the weights of links are rarely taken into account. In this paper, we use local similarity indices to estimate the likelihood of the existence of links in weighted networks, including Common Neighbor, Adamic-Adar Index, Resource Allocation Index, and their weighted versions. In both the unweighted and weighted cases, the resource allocation index performs the best. To our surprise, the weighted indices perform worse, which reminds us of the well-known Weak Tie Theory. Further extensive experimental study shows that the weak ties play a significant role in the link prediction problem, and to emphasize the contribution of weak ties can remarkably enhance the predicting accuracy.

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