Sentimental analysis states the use of Natural Language Processing (NLP). It is used to track the emotions or sentiments of the people based on a particular product or topic. The micro blogging websites like Facebook and Twitter plays an inevitable role in tracing these emotions. This study mainly focuses on fitting a model based on classification of Tweets as positive and negative using different filters namely Naive Bayesian and filtered classifiers using machine learning tool and to prove how effective and accurate the machine learning tool can be used in data mining to predict Tweets as positive and negative. It is observed that Naive Bayesian filter gives better results than filtered classifier for test data and further can be employed as a tool to study the opinions of people.
V. Reshma, Anand, S., and Maya L. Pai, “A Twitter Based Sentimental Approch On India’s Largest 4G Network “JIO””, Journal of Engineering and Applied Sciences, vol. 13, no. 5, pp. 4600-4603, 2018.