Which side are you on?: identifying perspectives at the document and sentence levels

  • Authors:
  • Wei-Hao Lin;Theresa Wilson;Janyce Wiebe;Alexander Hauptmann

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;University of Pittsburgh, Pittsburgh, PA;University of Pittsburgh, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
  • Year:
  • 2006

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Abstract

In this paper we investigate a new problem of identifying the perspective from which a document is written. By perspective we mean a point of view, for example, from the perspective of Democrats or Republicans. Can computers learn to identify the perspective of a document? Not every sentence is written strongly from a perspective. Can computers learn to identify which sentences strongly convey a particular perspective? We develop statistical models to capture how perspectives are expressed at the document and sentence levels, and evaluate the proposed models on articles about the Israeli-Palestinian conflict. The results show that the proposed models successfully learn how perspectives are reflected in word usage and can identify the perspective of a document with high accuracy.