Weighted network modules

Details Weighted network modules Weighted network modules

2007-03-27

arxiv.org/abs/cond-mat/0703706v1

New J. Phys. 9, 180 (2007)

Physics

Condensed Matter

Statistical Mechanics

19 pages, 7 figures

Scientific paper

10.1088/1367-2630/9/6/180

The inclusion of link weights into the analysis of network properties allows a deeper insight into the (often overlapping) modular structure of real-world webs. We introduce a clustering algorithm (CPMw, Clique Percolation Method with weights) for weighted networks based on the concept of percolating k-cliques with high enough intensity. The algorithm allows overlaps between the modules. First, we give detailed analytical and numerical results about the critical point of weighted k-clique percolation on (weighted) Erdos-Renyi graphs. Then, for a scientist collaboration web and a stock correlation graph we compute three-link weight correlations and with the CPMw the weighted modules. After reshuffling link weights in both networks and computing the same quantities for the randomised control graphs as well, we show that groups of 3 or more strong links prefer to cluster together in both original graphs.

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