Mining newsgroups using networks arising from social behavior Export

@inproceedings{citeulike:820132, address = {New York, NY, USA}, author = {Agrawal, Rakesh and Rajagopalan, Sridhar and Srikant, Ramakrishnan and Xu, Yirong}, booktitle = {WWW '03: Proceedings of the 12th international conference on World Wide Web}, citeulike-article-id = {820132}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=775227}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/775152.775227}, comment = {Recent advances in information retrieval over hyperlinked corpora have convincingly demonstrated that 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 into opposite camps. In contrast, methods based on statistical analysis of text yield low accuracy on such datasets because the vocabulary used by the two sides tends to be largely identical, and many newsgroup postings consist of relatively few words of text.}, doi = {10.1145/775152.775227}, isbn = {1581136803}, keywords = {community, linkage, sn}, pages = {529--535}, posted-at = {2006-08-28 20:40:06}, priority = {3}, publisher = {ACM Press}, title = {Mining newsgroups using networks arising from social behavior}, url = {http://dx.doi.org/10.1145/775152.775227}, year = {2003} }

TY - CONF ID - citeulike:820132 L3 - citeulike-article-id:820132 SN - 1581136803 AD - New York, NY, USA EP - 535 TI - Mining newsgroups using networks arising from social behavior PB - ACM Press T2 - WWW '03: Proceedings of the 12th international conference on World Wide Web SP - 529 KW - community KW - linkage KW - sn N1 - Recent advances in information retrieval over hyperlinked corpora have convincingly demonstrated that 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 into opposite camps. In contrast, methods based on statistical analysis of text yield low accuracy on such datasets because the vocabulary used by the two sides tends to be largely identical, and many newsgroup postings consist of relatively few words of text. AU - Agrawal, Rakesh AU - Rajagopalan, Sridhar AU - Srikant, Ramakrishnan AU - Xu, Yirong PY - 2003/// UR - http://dx.doi.org/10.1145/775152.775227 ER -