Mining newsgroups using networks arising from social behavior

Recent advances in information retrieval over hyperlinked corpora have convincinglydemonstratedthat links carry less noisy information than text. We investigate the feasibility of applying link-based methods in new applications domains. The specific application we consider is to partition authors into opposite camps within a given topic in the context of newsgroups. A typical newsgroup posting consists of one or more quoted lines from another posting followed by the opinion of the author. This social behavior gives rise to a network in which the vertices are individuals and the links represent "responded-to" relationships. An interesting characteristic of many newsgroups is that people more frequently respond to a message when they disagree than when they agree. This behavior is in sharp contrast to the WWW link graph, where linkage is an indicator of agreement or common interest. By analyzing the graph structure of the responses, we are able to effectively classify people i...

• Type: Conference
• Year: 2003
• Where: WWW
• Authors: Rakesh Agrawal, Sridhar Rajagopalan, Ramakrishnan Srikant, Yirong Xu
• Keywords: Internet Technology, Keywords Data Mining, Text Mining, WWW 2003, WWW Link Graph