Identifying expressions of emotion in text

  • Authors:
  • Saima Aman;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 and Institute of Computer Science, Polish Academy of Sciences, Warszawa, Poland

  • Venue:
  • TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
  • Year:
  • 2007

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Abstract

Finding emotions in text is an area of research with wide-ranging applications. We describe an emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in text. We introduce the annotation scheme and present results of an annotation agreement study on a corpus of blog posts. The average inter-annotator agreement on labeling a sentence as emotion or non-emotion was 0.76. The agreement on emotion categories was in the range 0.6 to 0.79; for emotion indicators, it was 0.66. Preliminary results of emotion classification experiments show the accuracy of 73.89%, significantly above the baseline.