Sentiment Analysis of Social Networking Websites using Gravitational Search Optimization Algorithm
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.
Year of publication: |
2018
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Authors: | Goel, Lavika ; Garg, Anubhav |
Published in: |
International Journal of Applied Evolutionary Computation (IJAEC). - IGI Global, ISSN 1942-3608, ZDB-ID 2696101-5. - Vol. 9.2018, 1 (01.01.), p. 76-85
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Publisher: |
IGI Global |
Subject: | Ant Colony Optimization Metaheuristic | Gravitational Search Algorithm | Sentiment Analysis | Swarm Intelligence |
Saved in:
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