Volume 9 Number 9 (Sep. 2014)
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JSW 2014 Vol.9(9): 2409-2416 ISSN: 1796-217X
doi: 10.4304/jsw.9.9.2409-2416

Community Detection in Social Networks Based on Influential Nodes

Chang Su1, Yukun Wang1, Lan Zhang2
1Chongqing University of Posts and Telecommunications, Chongqing, China
2Capital University of Economics and Business, Beijing, China


Abstract—Large-scale social networks emerged rapidly in recent years. Social networks have become complex networks. The structure of social networks is an important research area and has attracted much scientific interest. Community is an important structure in social networks. In this paper, we propose a community detection algorithm based on influential nodes. First, we introduce how to find influential nodes based on random walk. Then we combine the algorithm with order statistics theory to find community structure. We apply our algorithm in three classical data sets and compare to other algorithms. Our community detection algorithm is proved to be effective in the experiments. Our algorithm also has applications in data mining and recommendations.

Index Terms—Influential nodes, Social network, Community structure, Random walk, Order statistics

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Cite: Chang Su, Yukun Wang, Lan Zhang, "Community Detection in Social Networks Based on Influential Nodes," Journal of Software vol. 9, no. 9, pp. 2409-2416, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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