Opinion mining on the web by extracting subject-aspect-evaluation relations

Nozomi Kobayashi, Ryu Iida, Kentaro Inui, Yuji Matsumoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

This paper addresses the task of extracting opinions from a given document collection. Assuming that an opinion can be represented as a tuple (Subject, Aspect, Evaluation), we propose a computational method to extract such tuples from texts. In this method, the main task is decomposed into (a) the process of extracting Aspect-Evaluation pairs from a given text and (b) the process of judging whether an extracted pair expresses an opinion of the author. We apply machine-learning techniques to both subtasks. We also report on the results of our experiments and discuss future directions.

Original languageEnglish
Title of host publicationComputational Approaches to Analyzing Weblogs - Papers from the AAAI Spring Symposium, Technical Report
Pages86-91
Number of pages6
Publication statusPublished - 2006
Event2006 AAAI Spring Symposium - Stanford, CA, United States
Duration: 2006 Mar 272006 Mar 29

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-06-03

Other

Other2006 AAAI Spring Symposium
CountryUnited States
CityStanford, CA
Period06/3/2706/3/29

ASJC Scopus subject areas

  • Engineering(all)

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