Machine Learning
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Inferring and Visualizing Social Networks on Internet Relay Chat
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Lexical and Discourse Analysis of Online Chat Dialog
ICSC '07 Proceedings of the International Conference on Semantic Computing
Statistical analysis of the social network and discussion threads in slashdot
Proceedings of the 17th international conference on World Wide Web
Dialogue act tagging for instant messaging chat sessions
ACLstudent '05 Proceedings of the ACL Student Research Workshop
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The Internet contains an increasing number of online forums where consumers exchange product opinions. It is important for companies to know how consumers judge their products and how these opinions are spread by interactions throughout online forums. With this knowledge it is possible to recognize risks and chances. However, classical opinion research is very time consuming and only possible to a certain extent. This paper introduces a system which automatically extracts opinions and communication relationships in forums by text mining and identifies influential users and trends by social network analysis.