Thread specific features are helpful for identifying subjectivity orientation of online forum threads

Prakhar Biyani, Sumit Bhatia, Cornelia Caragea, Prasenjit Mitra

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

18 Scopus citations

Abstract

Subjectivity analysis has been actively used in various applications such as opinion mining of customer reviews in online review sites, question-answering in CQA sites, multi-document summarization, etc. However, there has been very little focus on subjectivity analysis in the domain of online forums. Online forums contain huge amounts of user-generated data in the form of discussions between forum members on specific topics and are a valuable source of information. In this work, we perform subjectivity analysis of online forum threads. We model the task as a binary classification of threads in one of the two classes: subjective and non-subjective. Unlike previous works on subjectivity analysis, we use several non-lexical thread-specific features for identifying subjectivity orientation of threads. We evaluate our methods by comparing them with several state-of-the-art subjectivity analysis techniques. Experimental results on two popular online forums demonstrate that our methods outperform strong baselines in most of the cases.

Original languageEnglish (US)
Title of host publication24th International Conference on Computational Linguistics - Proceedings of COLING 2012: Technical Papers
Pages295-310
Number of pages16
StatePublished - 2012
Event24th International Conference on Computational Linguistics, COLING 2012 - Mumbai, India
Duration: Dec 8 2012Dec 15 2012

Other

Other24th International Conference on Computational Linguistics, COLING 2012
Country/TerritoryIndia
CityMumbai
Period12/8/1212/15/12

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Language and Linguistics
  • Linguistics and Language

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