Sentiment intensity: is it a good summary indicator

  • Authors:

  • Mijail Kabadjov;Alexandra Balahur;Ester Boldrini

  • Affiliations:

  • Joint Research Centre, European Commission, Ispra, VA, Italy;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain

  • Venue:
  • LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
  • Year:
  • 2009

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Abstract

In this paper we address the question of whether "very positive" or "very negative" sentences from the perspective of sentiment analysis are "good" summary sentences from the perspective of text summarisation. We operationalise the concepts of very positive and very negative sentences by using the output of a sentiment analyser and evaluate how good a sentence is for summarisation by making use of standard text summarisation metrics and a corpus annotated for both salience and sentiment. In addition, we design and execute a statistical test to evaluate the aforementioned hypothesis. We conclude that the hypothesis does not hold, at least not based on our corpus data, and argue that summarising sentiment and summarising text are two different tasks which should be treated separately.