Language patterns in the learning of strategies from negotiation texts

  • Authors:
  • Marina Sokolova;Stan Szpakowicz

  • Affiliations:
  • School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada;School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada

  • Venue:
  • AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
  • Year:
  • 2006

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Abstract

The paper shows how to construct language patterns that signal influence strategies and tactical moves corresponding to such strategies. We apply corpus analysis methods to the extraction of certain multi-word patterns from the text data of electronic negotiations. The patterns thus acquired become features in the task of classifying those texts. A series of machine learning experiments predicts the negotiation outcome from the texts associated with first halves of negotiations. We compare the results with the classification of complete negotiations.