Finding communities in directed networks by PageRank random walk induced network embedding |
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Authors: | Darong Lai Hongtao Lu |
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Affiliation: | a Department of computer science and engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, 200240, Shanghai, China b CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, 200031, Shanghai, China |
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Abstract: | Community structure has been found to exist ubiquitously in many different kinds of real world complex networks. Most of the previous literature ignores edge directions and applies methods designed for community finding in undirected networks to find communities. Here, we address the problem of finding communities in directed networks. Our proposed method uses PageRank random walk induced network embedding to transform a directed network into an undirected one, where the information on edge directions is effectively incorporated into the edge weights. Starting from this new undirected weighted network, previously developed methods for undirected network community finding can be used without any modification. Moreover, our method improves on recent work in terms of community definition and meaning. We provide two simulated examples, a real social network and different sets of power law benchmark networks, to illustrate how our method can correctly detect communities in directed networks. |
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Keywords: | Directed network Community Random walk Network embedding Modularity |
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