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%.

Social media sites recently became popular, it is clear that it has major influence in society, and almost one third of the entire world are in social media. It became a platform where people express their feelings, share their ideas, wisdoms and give feedback of an event or a product, with help of new technology it gave us an opportunity to analyse these contents easily. Twitter being one of these sites, with full of people opinions, where one can truck sentiment express about different kind of topics, instead of wasting time and energy for long surveys, due to advance sentiment analysis we can now collect a huge data of opinions of people. Sentiment analysis was one of the major interesting research area nowadays. In this paper we focused Sentimental insight into the 2019 Kenya currency replacement. Kenya government has announced that the country currency is to be replace wıth new generatıon of bank notes, the government ordered the Kenyan citizen to return back the old 1000 shilling notes ($10) to bank by 1st October 2019, in a bid to fight against corruption and money laundering. Kenyans citizen expressed their reaction over new banknotes. We perform sentiment analysis of the tweets using Multinomial Naïve Bayes algorithm by utilizing data from one of the social media platform–Twitter and I have collected during this period of demonetization, 1122 tweets from twitter using web scrapper with help of twitter advance search.