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Subjectivity detection in spoken and written conversations

Published online by Cambridge University Press:  09 December 2010

GABRIEL MURRAY  and
GIUSEPPE CARENINI
GABRIEL MURRAY
Affiliation:
Department of Computer Science, 201-2366 Main Mall, University of British Columbia Vancouver, CanadaV6T 1Z4 emails: [email protected], [email protected]
GIUSEPPE CARENINI
Affiliation:
Department of Computer Science, 201-2366 Main Mall, University of British Columbia Vancouver, CanadaV6T 1Z4 emails: [email protected], [email protected]
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Abstract

In this work we investigate four subjectivity and polarity tasks on spoken and written conversations. We implement and compare several pattern-based subjectivity detection approaches, including a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-gram word sequences with varying levels of lexical instantiation. We compare the use of these learned patterns with an alternative approach of using a very large set of raw pattern features. We also investigate how these pattern-based approaches can be supplemented and improved with features relating to conversation structure. Experimenting with meeting speech and email threads, we find that our novel systems incorporating varying instantiation patterns and conversation features outperform state-of-the-art systems despite having no recourse to domain-specific features such as prosodic cues and email headers. In some cases, such as when working with noisy speech recognizer output, a small set of well-motivated conversation features performs as well as a very large set of raw patterns.

Type
Articles
Information
Natural Language Engineering , Volume 17 , Issue 3 , July 2011 , pp. 397 - 418
Copyright
Copyright © Cambridge University Press 2010

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