Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns

  title={Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns},
  author={Yejin Choi and Claire Cardie and Ellen Riloff and Siddharth Patwardhan},
Recent systems have been developed for sentiment classification, opinion recognition, and opinion analysis (e.g., detecting polarity and strength). We pursue another aspect of opinion analysis: identifying the sources of opinions, emotions, and sentiments. We view this problem as an information extraction task and adopt a hybrid approach that combines Conditional Random Fields (Lafferty et al., 2001) and a variation of AutoSlog (Riloff, 1996a). While CRFs model source identification as a… CONTINUE READING
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  • The resulting system identifies opinion sources with 79.3% precision and 59.5% recall using a head noun matching measure, and 81.2% precision and 60.6% recall using an overlap measure.


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