Assessing sentiment of text by semantic dependency and contextual valence analysis

Mostafa Al Masum Shaikh, Helmut Prendinger, Ishizuka Mitsuru

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

50 Citations (Scopus)

Abstract

Text is not only an important medium to describe facts and events, but also to effectively communicate information about the writer's (positive or negative) sentiment underlying an opinion, and an affect or emotion (e.g. happy, fearful, surprised etc.). We consider sentiment assessment and emotion sensing from text as two different problems, whereby sentiment assessment is a prior task to emotion sensing. This paper presents an approach to sentiment assessment, i.e. the recognition of negative or positive sense of a sentence. We perform semantic dependency analysis on the semantic verb frames of each sentence, and apply a set of rules to each dependency relation to calculate the contextual valence of the whole sentence. By employing a domain-independent, rule-based approach, our system is able to automatically identify sentence-level sentiment. Empirical results indicate that our system outperforms another state-of-the-art approach.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages191-202
Number of pages12
Volume4738 LNCS
Publication statusPublished - 2007
Externally publishedYes
Event2nd International Conference on Affective Computing and Intelligent Interaction, ACII 2007 - Lisbon
Duration: 2007 Sep 122007 Sep 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4738 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Conference on Affective Computing and Intelligent Interaction, ACII 2007
CityLisbon
Period07/9/1207/9/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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  • Cite this

    Shaikh, M. A. M., Prendinger, H., & Mitsuru, I. (2007). Assessing sentiment of text by semantic dependency and contextual valence analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4738 LNCS, pp. 191-202). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4738 LNCS).