Enhancing opinion extraction by automatically annotated lexical resources (Extended version)

Andrea Esuli, Fabrizio Sebastiani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper we tackle an opinion extraction (OE) task, i.e., identifying in a text each expression of subjectivity, the subject expressing it, and its possible target. We especially focus on how lexical resources specifically developed for opinion mining could be used to improve the performance of an opinion extraction system. We report results, complete with statistical significance tests and inter-annotator agreement data, on two manually annotated corpora, one of English and one of Italian texts. We evaluate our results using standard evaluation measures and also using a new evaluation measure we have recently proposed.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages500-511
Number of pages12
Volume6562 LNAI
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event4th Language and Technology Conference, LTC 2009 - Poznan
Duration: 6 Nov 20098 Nov 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6562 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th Language and Technology Conference, LTC 2009
CityPoznan
Period6/11/098/11/09

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Esuli, A., & Sebastiani, F. (2011). Enhancing opinion extraction by automatically annotated lexical resources (Extended version). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6562 LNAI, pp. 500-511). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6562 LNAI). https://doi.org/10.1007/978-3-642-20095-3_46