Vocabulary choice as an indicator of perspective

Authors:
Beata Beigman Klebanov;Eyal Beigman;Daniel Diermeier
Affiliations:
Northwestern University and Washington University in St. Louis;Northwestern University and Washington University in St. Louis;Northwestern University and Washington University in St. Louis
Venue:
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Year:
2010

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Abstract

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.