Vocabulary Choice as an Indicator of Perspective

نویسندگان

  • Beata Beigman Klebanov
  • Eyal Beigman
  • Daniel Diermeier
چکیده

We establish the following characteristics of the task of perspective classification: (a) using term frequencies in a document does not improve classification achieved with absence/presence features; (b) for datasets allowing the relevant comparisons, a small number of top features is found to be as effective as the full feature set and indispensable for the best achieved performance, testifying to the existence of perspective-specific keywords. We relate our findings to research on word frequency distributions and to discourse analytic studies of perspective.

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تاریخ انتشار 2010