Support or oppose? Classifying positions in online debates from reply activities and opinion expressions

Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference

Volumn 2, Issue , 2010, Pages 869-875

  Murakami, Akiko ^a,b   Raymond, Rudy ^a  

^a IBM RESEARCH TOKYO   (Japan)

^b UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

LOCAL INFORMATION; TEXTUAL CONTENT;

COMPUTATIONAL LINGUISTICS;

EID: 80053413369     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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3. Galley, Michel, Kathleen McKeown, Julia Hirschberg, and Elizabeth Shriberg. 2004. Identifying agreement and disagreement in conversational speech: use of bayesian networks to model pragmatic dependencies. In ACL'04: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, pages 669-676, Morristown, NJ, USA. Association for Computational Linguistics.
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6. Murakami, Akiko, Katashi Nagao, and Koichi Takeda. 2001. Discussion Mining: Knowledge discovery from online discussion records. In NLPRS Workshop XML and NLP, 2001.
7. Murakami, Akiko, Tetsuya Nasukawa, Fusashi Nakamura, Hironori Takeuchi, Risa Nishiyama, Pnina Veisberg, and Hideo Watanabe. 2007. Innovation-Jam: Analysis of online discussion records using text mining technology. In International Workshop on Intercultual Collaboration 2007 (IWIC2007).
8. Rendl, Franz, Giovanni Rinaldi, and Angelika Wiegele. 2010. Solving Max-Cut to optimality by intersecting semidefinite and polyhedral relaxations. Math. Programming, 121(2):307.
9. Thomas, Matt, Bo Pang, and Lillian Lee. 2006. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pages 327-335, Sydney, Australia, July. Association for Computational Linguistics.