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|Title:||Challenges and Solutions in the Opinion Summarization of User-generated Contents|
|Authors:||BALAHUR DOBRESCU ALEXANDRA; KABADJOV Mijail; STEINBERGER JOSEF; STEINBERGER Ralf; MONTOYO Andrés|
|Citation:||JOURNAL OF INTELLIGENT INFORMATION SYSTEMS vol. 39 no. 2 p. 375-398|
|Type:||Articles in periodicals and books|
|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:||Space, Security and Migration|
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