Detect community structure from the Enron Email Corpus Based on Link Mining

Authors:
Rong Qian;Wei Zhang;Bingru Yang
Affiliations:
University of Science and Technology Beijing, China;University of Science and Technology Beijing, China;University of Science and Technology Beijing, China
Venue:
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Year:
2006

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Abstract

There have been considerable recent interest algorithms for finding communities in networks. This paper presents an algorithm based on link mining. The algorithm is very fast, since calculating the clustering coefficient can be done with local information only. With the algorithm, the community structure from the Enron email corpus is detected. And the visualization of the graph is showed.