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Exploiting Chi Square Method for Sentiment Analysis of Product Reviews

Author

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  • Nilesh M. Shelke

    (Priyadarshini Indira Gandhi College of Engineering, Nagpur, India)

  • Shrinivas P. Deshpande

    (DCPE, HVPM, Amravati, India)

Abstract

Sentiment analysis is an extension of data mining which employs natural language processing and information extraction task to recognize people's opinion towards entities such as products, services, issues, organizations, individuals, events, topics, and their attributes. It gives the summarized opinion of a writer or speaker. It has received lot of attention due to increasing number of posts/tweets on social sites. The proposed system is meant to classify a given text of review into positive, negative, or the neutral category. Primary objective of this article is to provide a method of exploiting permutation and combination and chi values for sentiment analysis of product reviews. Publicly available freely dictionary SentiWordNet 3.0 has been used for review classification. The proposed system is domain independent and context aware. Another objective of the proposed system is to identify the feature specific intensity with which reviewer has expressed his opinion. Effectiveness of the proposed system has been verified through performance matrix and compared with other research work.

Suggested Citation

  • Nilesh M. Shelke & Shrinivas P. Deshpande, 2018. "Exploiting Chi Square Method for Sentiment Analysis of Product Reviews," International Journal of Synthetic Emotions (IJSE), IGI Global, vol. 9(2), pages 76-93, July.
    • Handle: RePEc:igg:jse000:v:9:y:2018:i:2:p:76-93
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