Vocabulary Choice as an Indicator of Perspective

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.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Beata Beigman Klebanov, Eyal Beigman, Daniel Diermeier
• Keywords: ACL 2010, Computational Linguistics, Relevant Comparisons, Term Frequencies, Word Frequency Distributions