Title: Challenges and Solutions in the Opinion Summarization of User-generated Contents
Authors: BALAHUR DOBRESCU ALEXANDRAKABADJOV MijailSTEINBERGER JOSEFSTEINBERGER RalfMONTOYO Andrés
Citation: JOURNAL OF INTELLIGENT INFORMATION SYSTEMS vol. 39 no. 2 p. 375-398
Publisher: SPRINGER
Publication Year: 2012
JRC N°: JRC67503
ISSN: 0925-9902
URI: http://www.springerlink.com/content/5750629542266720/
http://publications.jrc.ec.europa.eu/repository/handle/JRC67503
DOI: 10.1007/s10844-011-0194-z
Type: Articles in Journals
Abstract: The present is marked by the influence of the Social Web on societies and people worldwide. In this context, users generate large amounts of data, especially containing opinion, which has been proven useful for many real-world applications. In order to extract knowledge from the user-generated content, automatic methods must be developed. In this paper, we present different approaches to summarizing opinion from blogs and reviews. We apply these approaches to: a) identify positive and negative opinions in blog threads in order to produce a list of arguments in favor and against a given topic and b) summarize the opinion expressed in reviews. Subsequently, we evaluate the proposed methods on two distinct datasets and analyze the quality of the obtained results, as well as discuss the errors produced. Finally, we conclude that the proposed approaches are appropriate in the context of opinion summarization.
JRC Institute:Institute for the Protection and Security of the Citizen

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