Co-training over Domain-independent and Domain-dependent features for sentiment analysis of an online cancer support community

Prakhar Biyani, Cornelia Caragea, Prasenjit Mitra, Chong Zhou, John Yen, Greta E. Greer, Kenneth Portier

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

25 Citations (Scopus)

Abstract

Sentiment analysis has been widely researched in the domain of online review sites with the aim of getting summarized opinions of product users about different aspects of the products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users in online health communities such as cancer support forums, etc. Online health communities act as a medium through which people share their health concerns with fellow members of the community and get social support. Identifying sentiments expressed by members in a health community can be helpful in understanding dynamics of the community such as dominant health issues, emotional impacts of interactions on members, etc. In this work, we perform sentiment classification of user posts in an online cancer support community (Cancer Survivors Network). We use Domain-dependent and Domain-independent sentiment features as the two complementary views of a post and use them for post classification in a semi-supervised setting using the co-training algorithm. Experimental results demonstrate effectiveness of our methods.

Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
PublisherAssociation for Computing Machinery
Pages413-417
Number of pages5
ISBN (Print)9781450322409
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013 - Niagara Falls, ON, Canada
Duration: 25 Aug 201328 Aug 2013

Publication series

NameProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013

Other

Other2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
CountryCanada
CityNiagara Falls, ON
Period25/8/1328/8/13

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Keywords

  • Co-training
  • Direct emotional support
  • Indirect emotional support
  • Online health community
  • Sentiment analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this

Biyani, P., Caragea, C., Mitra, P., Zhou, C., Yen, J., Greer, G. E., & Portier, K. (2013). Co-training over Domain-independent and Domain-dependent features for sentiment analysis of an online cancer support community. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013 (pp. 413-417). (Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013). Association for Computing Machinery. https://doi.org/10.1145/2492517.2492606