Author(s): Pal Deka and Manash Pratim Barman

Abstract: Sentiment analysis is the term used to understand the sentiments of the people or individuals. The sentiments of the investors towards certain stocks and stock exchanges could be classified into positive, negative and neutral. Twitter is one such social networking platforms used to express such sentiments. Here in this study, perceptions or sentiments of the investors towards one of the India’s largest stock exchange is examined. The tweets regarding #National Stock Exchange, India were extracted from the twitter platform from 2016-2021. The results shows that the neutral sentiment tweets were highest in number than positive and negative tweets during this period of time. Further the study also performed sentiment group classification. Multinomial logistic regression, Naïve Bayes and Support vector machine classification algorithms was considered. Among these learning algorithms, accuracy score of support vector machine algorithm was found better in classification of the tweets. The F-1 score of support vector machine algorithm was satisfactory then rest of the algorithms.

Pages: 90-93 | Views: 60 | Downloads: 9

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