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http://dx.doi.org/10.3745/KTCCS.2013.2.5.209

Local Information-based Betweenness Centrality to Identify Important Nodes in Social Networks  

Shon, Jin Gon (한국방송통신대학교 컴퓨터과학과)
Kim, Yong-Hwan (한국기술교육대학교 컴퓨터공학부)
Han, Youn-Hee (한국기술교육대학교 컴퓨터공학부)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.2, no.5, 2013 , pp. 209-216 More about this Journal
Abstract
In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.
Keywords
Social Network Analysis; Betweenness Centrality; Local Information; Expanded Ego Network;
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