INSIGHT Galway: Syntactic and Lexical Features for Aspect Based Sentiment Analysis

نویسندگان

  • Sapna Negi
  • Paul Buitelaar
چکیده

This work analyses various syntactic and lexical features for sentence level aspect based sentiment analysis. The task focuses on detection of a writer’s sentiment towards an aspect which is explicitly mentioned in a sentence. The target sentiment polarities are positive, negative, conflict and neutral. We use a supervised learning approach, evaluate various features and report accuracies which are much higher than the provided baselines. Best features include unigrams, clauses, dependency relations and SentiWordNet polarity scores.

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تاریخ انتشار 2014