Predicting the Semantic Orientation of Adjectives

V. Hatzivassiloglou,K. McKeown

Published 1997 in Annual Meeting of the Association for Computational Linguistics

ABSTRACT

We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. Evaluations on real data and simulation experiments indicate high levels of performance: classification precision is more than 90% for adjectives that occur in a modest number of conjunctions in the corpus.

PUBLICATION RECORD

  • Publication year

    1997

  • Venue

    Annual Meeting of the Association for Computational Linguistics

  • Publication date

    1997-07-07

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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