“Follow the Leader”: A Centrality Guided Clustering and Its Application to Social Network Analysis
Within graph theory and network analysis, centrality of a vertex measures the relative importance of a vertex within a graph. The centrality plays key role in network analysis and has been widely studied using different methods. Inspired by the idea of vertex centrality, a novel centrality guided cl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/368568 |
| Summary: | Within graph theory and network analysis, centrality of a vertex measures the relative importance of a
vertex within a graph. The centrality plays key role in network analysis and has been widely studied
using different methods. Inspired by the idea of vertex centrality, a novel centrality guided clustering
(CGC) is proposed in this paper. Different from traditional clustering methods which usually choose the
initial center of a cluster randomly, the CGC clustering algorithm starts from a “LEADER”—a vertex
with the highest centrality score—and a new “member” is added into the same cluster as the “LEADER” when
some criterion is satisfied. The CGC algorithm also supports overlapping membership. Experiments on
three benchmark social network data sets are presented and the results indicate that the proposed CGC
algorithm works well in social network clustering. |
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| ISSN: | 1537-744X |