Identifying Influential Edges by Node Influence Distribution and Dissimilarity Strategy

Yanjie Xu, Tao Ren and Shixiang Sun
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Yanjie Xu: Software College, Northeastern University, Shenyang 110169, China
Tao Ren: Software College, Northeastern University, Shenyang 110169, China
Shixiang Sun: Software College, Northeastern University, Shenyang 110169, China

Mathematics, 2021, vol. 9, issue 20, 1-13

Abstract: Identifying influential edges in a complex network is a fundamental topic with a variety of applications. Considering the topological structure of networks, we propose an edge ranking algorithm DID (Dissimilarity Influence Distribution), which is based on node influence distribution and dissimilarity strategy. The effectiveness of the proposed method is evaluated by the network robustness R and the dynamic size of the giant component and compared with well-known existing metrics such as Edge Betweenness index, Degree Product index, Diffusion Intensity and Topological Overlap index in nine real networks and twelve BA networks. Experimental results show the superiority of DID in identifying influential edges. In addition, it is verified through experimental results that the effectiveness of Degree Product and Diffusion Intensity algorithm combined with node dissimilarity strategy has been effectively improved.

Keywords: complex network; influence distribution; dissimilarity strategy; edge ranking (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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