SENTIMENT ANALYSIS MODEL FOR TWITTER ON COVID-19 VACCINE

Francisca Oladipo (), Prosper Akarah () and Andrew Ohieku ()
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Francisca Oladipo: Federal University Lokoja, Nigeria
Andrew Ohieku: Capital Science Academy, Nigeria

Journal of Information Systems & Operations Management, 2022, vol. 16, issue 1, 209-230

Abstract: Sentiment analysis is a classification technique that specializes in categorizing a body of texts into various emotions. This categorization had proven to be handy in classifying tweets into positive, negative, or neutral emotions. The focus of this paper is to determine the sentiment analysis of Indians and Americans. Using a lexicon-based analytic architecture and a dataset used for this research work was gotten from an online database Kaggle dataset called “All COVID-19 Vaccines Tweets†. The dataset contains 125,906 entries with 16 columns with every country in the world from which tweets with location marked India and USA/United States were extracted. The analysis was done in Python Programming Software with the application of a python module TextBlob. The result shows that the Americans have larger positive sentiments over the Indians with 3.26%.

Date: 2022
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