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Lexical-Syntactical Patterns for Subjectivity Analysis of Social Issues

  • Mostafa Karamibekr
  • Ali Akbar Ghorbani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

Subjectivity analysis investigates attitudes, feelings, and expressed opinions about products, services, topics, or issues. As the basic task, it classifies a text as subjective or objective. While subjective text expresses opinions about an object or issue using sentiment expressions, objective text describes an object or issue considering their facts. The presence of sentiment terms such as adjectives, nouns and adverbs in products reviews usually implicates their subjectivity, but for comments about social issues, it is more complicated and sentiment phrases and patterns are more common and descriptive. This paper proposes a lexical-syntactical structure for subjective patterns for subjectivity analysis in social domains. It is employed and evaluated for subjectivity and sentiment classification at the sentence level. The proposed method outperforms some similar works. Moreover, its reasonable F-measure implicates its usability in applications like sentiment summarization and opinion question answering.

Keywords

Sentiment analysis Subjectivity analysis Subjectivity classification Subjective pattern 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Mostafa Karamibekr
    • 1
  • Ali Akbar Ghorbani
    • 1
  1. 1.Faculty of Computer ScienceUniversity of New BrunswickFrederictonCanada

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