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Sentiment Analysis of Social Networking Websites using Gravitational Search Optimization Algorithm

Author

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  • Lavika Goel

    (Department of Computer Science and Information Systems, Birla Institute of Technology and Science (BITS), Pilani, Rajasthan, India)

  • Anubhav Garg

    (Birla Institute of Technology and Science (BITS), Pilani, India)

Abstract

Analysing sentiments of various online communities have become now an interesting topic of research and industry. The behaviour of online communities resembles that of a swarm. This article presents a Gravitational Search algorithmic approach for sentiment analysis of online communities, and an optimization algorithm which is based on the mass interactions and law of gravity. In the end, the authors present comparisons with other techniques, particularly ant colony optimization and Naive Bayes classification for sentiment analysis.

Suggested Citation

  • Lavika Goel & Anubhav Garg, 2018. "Sentiment Analysis of Social Networking Websites using Gravitational Search Optimization Algorithm," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 9(1), pages 76-85, January.
    • Handle: RePEc:igg:jaec00:v:9:y:2018:i:1:p:76-85
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