ISSN: 0973-7510

E-ISSN: 2581-690X

R. Satheesh Kumar1 and S.Vijayan2
1Department of Information Technology , Hindusthan College of Engineering & Technology, Coimbatore , Tamilnadu , India.
2Surya Engineering College, Perundurai, Erode, Tamilnadu, India.
J Pure Appl Microbiol. 2015;9(Spl. Edn. Aug.):37-45
© The Author(s). 2015
Received: 12/05/2015 | Accepted: 30/06/2015 | Published: 31/08/2015
Abstract

Various websites today provide medical information and this information can either be affective or informative. For example the blogs in Mayo clinic or Net doctor contains both information which are facts and information which are opinions from a fellow patient, doctor or nurse who try to analyze the given query and give an opinion. Similarly a site visitor can give his opinion without any knowledge on the subject. This paper proposes a semantic based feature extraction for automatically classifying affective and informative posts. The proposed semantic based feature selection uses SentiWordNet which is a lexical resource of WordNet database extracted terms and is available for research purposes. Results achievedshow that SentiWordNet is a good resource for sentiment opinion classification.

Keywords

Opinion Mining, Semantic based feature selection, SentiWordNet and sentiment classification

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© The Author(s) 2015. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.