Title: Sentiment Intensity: Is It a Good Summary Indicator?
Authors: KABADJOV MIJAILBALAHUR AlexandraBOLDRINI Ester
Citation: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE vol. 6562 p. 203-212
Publisher: SPRINGER-VERLAG BERLIN
Publication Year: 2011
JRC N°: JRC65692
ISSN: 0302-9743
URI: http://www.springerlink.com/content/h82q1652134642k7/
http://publications.jrc.ec.europa.eu/repository/handle/JRC65692
DOI: 10.1007/978-3-642-20095-3_19
Type: Articles in Journals
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.
JRC Institute:Institute for the Protection and Security of the Citizen

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