Developing evaluation model of topical term for document-level sentiment classification

Yi Hu, Wenjie Li, Qin Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Sentiment classification is used to identify whether the opinion expressed in a document is positive or negative. In this paper, we present an evaluation modeling approach to document-level sentiment classification. The motivation of this work stems from the observation that the global document classification can benefit greatly by learning how a topical term is evaluated in its local sentence context. Two sentence-level sentiment evaluation models, namely positive and negative models, are constructed for each topical term. When analyzing a document, the evaluation models generate divergence to support sentence classification that in turn can be used to decide on the whole document classification collectively. When evaluated on a public available movie review corpus, the experimental results are comparable with the ones published. This is quite encouraging to us and motivates us to further investigate how to develop more effective evaluation models in the future.
Original languageEnglish
Title of host publicationPRICAI 2008
Subtitle of host publicationTrends in Artificial Intelligence - 10th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Pages175-186
Number of pages12
DOIs
Publication statusPublished - 1 Dec 2008
Event10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008 - Hanoi, Viet Nam
Duration: 15 Dec 200819 Dec 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5351 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008
CountryViet Nam
CityHanoi
Period15/12/0819/12/08

Keywords

  • Evaluation model
  • Maximum spanning tree
  • Sentiment classification
  • Topical term

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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