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http://dx.doi.org/10.5351/KJAS.2011.24.2.401

Monte-Carlo Methods for Social Network Analysis  

Huh, Myung-Hoe (Department of Statistics, Korea University)
Lee, Yong-Goo (Department of Statistics, ChungAng University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.2, 2011 , pp. 401-409 More about this Journal
Abstract
From a social network of n nodes connected by l lines, one may produce centrality measures such as closeness, betweenness and so on. In the past, the magnitude of n was around 1,000 or 10,000 at most. Nowadays, some networks have 10,000, 100,000 or even more than that. Thus, the scalability issue needs the attention of researchers. In this short paper, we explore random networks of the size around n = 100,000 by Monte-Carlo method and propose Monte-Carlo algorithms of computing closeness and betweenness centrality measures to study the small world properties of social networks.
Keywords
Social network analysis; closeness centrality; betweenness centrality; small world; data scalability; Monte Carlo method;
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