Predicting subjectivity orientation of online forum threads

Prakhar Biyani, Cornelia Caragea, Prasenjit Mitra

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

10 Scopus citations

Abstract

Online forums contain huge amounts of valuable information in the form of discussions between forum users. The topics of discussions can be subjective seeking opinions of other users on some issue or non-subjective seeking factual answer to specific questions. Internet users search these forums for different types of information such as opinions, evaluations, speculations, facts, etc. Hence, knowing subjectivity orientation of forum threads would improve information search in online forums. In this paper, we study methods to analyze subjectivity of online forum threads. We build binary classifiers on textual features extracted from thread content to classify threads as subjective or non-subjective. We demonstrate the effectiveness of our methods on two popular online forums.

Original languageEnglish (US)
Title of host publicationComputational Linguistics and Intelligent Text Processing - 14th International Conference, CICLing 2013, Proceedings
Pages109-120
Number of pages12
EditionPART 2
DOIs
StatePublished - Apr 3 2013
Event14th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2013 - Samos, Greece
Duration: Mar 24 2013Mar 30 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7817 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2013
CountryGreece
CitySamos
Period3/24/133/30/13

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Biyani, P., Caragea, C., & Mitra, P. (2013). Predicting subjectivity orientation of online forum threads. In Computational Linguistics and Intelligent Text Processing - 14th International Conference, CICLing 2013, Proceedings (PART 2 ed., pp. 109-120). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7817 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-37256-8_10