Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Online community search using thread structure
Proceedings of the 18th ACM conference on Information and knowledge management
Educational Question Answering based on Social Media Content
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Exploiting thread structures to improve smoothing of language models for forum post retrieval
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Product review summarization from a deeper perspective
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
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Online forums have become a popular source of information due to the unique nature of information they contain. Internet users use these forums to get opinions of other people on issues and to find factual answers to specific questions. Topics discussed in online forum threads can be subjective seeking personal opinions or non-subjective seeking factual information. Hence, knowing subjectivity orientation of threads would help forum search engines to satisfy user's information needs more effectively by matching the subjectivities of user's query and topics discussed in the threads in addition to lexical match between the two. We study methods to analyze the subjectivity of online forum threads. Experimental results on a popular online forum demonstrate the effectiveness of our methods.