Paper: Identifying Perspectives At The Document And Sentence Levels Using Statistical Models

ACL ID N06-3005
Title Identifying Perspectives At The Document And Sentence Levels Using Statistical Models
Venue Human Language Technologies
Session Doctoral Consortium
Year 2006
Authors
  • Wei-Hao Lin (Carnegie Mellon University, Pittsburgh PA)

In this paper we investigate the problem of identifying the perspective from which a document was written. By perspective we mean a point of view, for example, from the perspective of Democrats or Repub- licans. Can computers learn to identify the perspective of a document? Further- more, can computers identify which sen- tences in a document strongly convey a particular perspective? We develop sta- tistical models to capture how perspec- tives are expressed at the document and sentence levels, and evaluate the proposed models on a collection of articles on the Israeli-Palestinian conflict. The results show that the statistical models can suc- cessfully learn how perspectives are re- flected in word usage and identify the per- spective of a document with very high ac- curacy.