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Computational Intelligence and Neuroscience
Volume 2015, Article ID 715730, 9 pages
http://dx.doi.org/10.1155/2015/715730
Research Article

Sentiment Analysis Using Common-Sense and Context Information

1Department of Computer Science & Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), Jaipur 302017, India
2Department of Computer and Engineering, Malaviya National Institute of Technology (MNIT), Malviya Nagar, Jaipur 302017, India

Received 19 August 2014; Revised 19 February 2015; Accepted 23 February 2015

Academic Editor: Christian W. Dawson

Copyright © 2015 Basant Agarwal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods.