Sentiment Analysis on Twitter by Using TextBlob for Natural Language Processing
Ditiman Hazarika, Gopal Konwar, Shuvam Deb, Dibya Jyoti Bora
DOI: http://dx.doi.org/10.15439/2020KM20
Citation: Proceedings of the 2020 International Conference on Research in Management & Technovation, Shivani Agarwal, Darrell Norman Burrell, Vijender Kumar Solanki (eds). ACSIS, Vol. 24, pages 63–67 (2020)
Abstract. The Internet has become an innovative platform regarding online learning, exchanging content, sharing views. In this paper, we will use Twitter as our social networking platform. Sentiment analysis on Twitter is based on opinion mining on posts to obtain the user's point of view. The leading goal deals with how opinion mining techniques can be accessed to analyze some of the tweets in many reports involving various types of tweet languages on Twitter and classify its polarity. Practical implication shows that the proposed machine learning classifiers are efficient and highly accurate
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