Sentiment Analysis on New Currency in Kenya using Twitter Dataset

Abstract

Social media sites recently became popular, it is clear that it has major influence in society. Twitter is one of these sites, full of people’s opinions, where one can truck sentiment express about different kinds of topics. Sentiment analysis is one of the major interesting research areas nowadays. In this paper, we focused on Sentimental insight into the 2019 Kenya currency replacement. Kenyans citizens expressed their reaction over new banknotes. We perform sentiment analysis of the tweets from twitter using the Multinomial Naïve Bayes algorithm. We split our dataset using k-folder cross validation since we had limited amounts of data, so to achieve unbiased prediction of the model we obtained an average accuracy of 75.3%.