Unsupervised subjectivity-lexicon generation based on vector space model for multi-dimensional opinion analysis in blogosphere

Hsieh Wei Chen, Kuan Rong Lee, Hsun Hui Huang, Yau-Hwang Kuo

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

3 Citations (Scopus)

Abstract

This paper presents an unsupervised framework to generate a vector-space-modeled subjectivity-lexicon for multi-dimensional opinion mining and sentiment analysis, such as criticism analysis, for which the traditional polarity analysis alone is not adequate. The framework consists of four major steps: first, creating a dataset by crawling blog posts of fiction reviews; secondly, creating a "subjectivity-term to object" matrix, with each subjectivity-term being modeled as a dimension of a vector space; thirdly, feature-transforming each subjectivity-term into the new feature-space to create the final multi-dimensional subjectivity-lexicon (MDSL); and fourthly, using the generated MDSL for opinion analysis. In the experiments, it shows that the improvement by the feature transform can be up to 31% in terms of the entropy of features. In addition, the subjectivity-terms and objects are also successfully and reasonably clustered in the demonstration of fiction review (literary criticism) analysis.

Original languageEnglish
Title of host publicationAdvanced Intelligent Computing Theories and Applications - 6th International Conference on Intelligent Computing, ICIC 2010, Proceedings
Pages372-379
Number of pages8
DOIs
Publication statusPublished - 2010 Oct 29
Event6th International Conference on Intelligent Computing, ICIC 2010 - Changsha, China
Duration: 2010 Aug 182010 Aug 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6215 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Intelligent Computing, ICIC 2010
CountryChina
CityChangsha
Period10-08-1810-08-21

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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