Exploring the community structure of newsgroups

d Abstract] Christian Borgs Jennifer Chayes Mohammad Mahdian Amin Saberi We propose to use the community structure of Usenet for organizing and retrieving the information stored in newsgroups. In particular, we study the network formed by crossposts, messages that are posted to two or more newsgroups simultaneously. We present what is, to our knowledge, by far the most detailed data that has been collected on Usenet cross-postings. We analyze this network to show that it is a small-world network with significant clustering. We also present a spectral algorithm which clusters newsgroups based on the cross-post matrix. The result of our clustering provides a topical classification of newsgroups. Our clustering gives many examples of significant relationships that would be missed by semantic clustering methods. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval; G.2.2 [Discrete Mathematics]: Graph Theory General Terms Algorithms...

• Type: Conference
• Year: 2004
• Where: KDD
• Authors: Christian Borgs, Jennifer T. Chayes, Mohammad Mahdian, Amin Saberi
• Keywords: Data Mining, KDD 2004, Keywords Spectral Method, Semantic Clustering Methods, Significant Clustering