Title: Enhancing sentiment analysis using enhanced whale optimisation algorithm

Authors: Abdul Salam Mohammed; Vishal Shukla; Avinash Chandra Pandey

Addresses: Skyline University College, Dubai, UAE ' Institute of Management Studies, Ghaziabad, India ' Jaypee Institute of Information Technology, Noida, India

Abstract: Sentiment analysis is discovers the opinion of users with respect to some sentimental topics commonly available at the online social platforms. Twitter is one of the popular social networking sites where people express their views about any topic in the form of tweets. These Twitter posts are analysed to obtain the viewpoints of users by using clustering-based methods. However, due to the subjective nature of the sentimental datasets metaheuristic clustering methods outruns the conventional methods for sentiment analysis. Therefore, in this paper, a new metaheuristic method based on the whale optimisation method has been introduced. The proposed method finds the optimal cluster centres from sentimental data. The performance of proposed method has been tested on Twitter datasets and compared in respect to mean accuracy, mean recall, and mean precision, mean fitness with state-of-the-art approaches. The proposed method attains the highest accuracy for most of the datasets compared to the state-of-the-art.

Keywords: sentiment analysis; metaheuristic methods; natural language processing; NLP; clustering.

DOI: 10.1504/IJIIDS.2020.109456

International Journal of Intelligent Information and Database Systems, 2020 Vol.13 No.2/3/4, pp.208 - 230

Received: 18 Apr 2019
Accepted: 23 Sep 2019

Published online: 26 Aug 2020 *

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