Journal of Intelligent Information Systems

, Volume 39, Issue 2, pp 375–398

Challenges and solutions in the opinion summarization of user-generated content

  • Alexandra Balahur
  • Mijail Kabadjov
  • Josef Steinberger
  • Ralf Steinberger
  • Andrés Montoyo
Article

DOI: 10.1007/s10844-011-0194-z

Cite this article as:
Balahur, A., Kabadjov, M., Steinberger, J. et al. J Intell Inf Syst (2012) 39: 375. doi:10.1007/s10844-011-0194-z

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 user-generated content, automatic methods must be developed. In this paper, we present different approaches to multi-document summarization of 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. Although much remains to be done, the approaches we propose obtain encouraging results and point to clear directions in which further improvements can be made.

Keywords

Opinion mining Blog threads User-generated content Sentiment analysis Opinion summarization 

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Alexandra Balahur
    • 1
  • Mijail Kabadjov
    • 1
  • Josef Steinberger
    • 1
  • Ralf Steinberger
    • 1
  • Andrés Montoyo
    • 2
  1. 1.European Commission Joint Research CentreIspraItaly
  2. 2.DLSIUniversity of AlicanteAlicanteSpain

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