Copyright: © the author(s), publisher and licensee Technoscience Academy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited International Journal of Scientific Research in Science, Engineering and Technology Print ISSN: 2395-1990 | Online ISSN : 2394-4099 (www.ijsrset.com) doi : https://doi.org/10.32628/IJSRSET2310281 665 Twitter Sentiment Analysis using Machine Learning G. Manikandan, M. Robinson Joel, S. Lidiya Jones Raj, D. Madlin Jency Department of Information Technology, Kings Engineering College, Chennai, India A R T I C L E I N F O A B S T R A C T Article History: Accepted: 05 April 2023 Published: 27 April 2023 Social media makes it easier for people to communicate with one another online. Social media encompasses a wide range of applications and platforms, including Facebook for entertainment, Instagram for youth, Twitter for social and political, and YouTube, that let users share information, communicate online, and create communities. More than 4.7 billion individuals, or nearly 60% of the world's population, utilise social media. Twitter is a popular social media platform where users may express their feelings and opinions. In order to determine user sentiments, this Twitter sentiment analysis study uses sentiment analysis to data from tweets on the social media site. A whole new set of problems, such as the usage of slang and acronyms, are brought about by the relatively small size of the tweet format. Our objective is to carry out research on Twitter sentiment analysis while outlining the methodology, models, and generalised Python-based approach that was employed. Keywords: Classification, Data Preprocessing, Machine Learning, Sentiment Analysis. Publication Issue Volume 10, Issue 2 March-April-2023 Page Number 665-669 I. INTRODUCTION Users of the social networking site Twitter can submit tweets, which are brief communications that can have a maximum character count of 280. Users can follow other users, and a chronological feed will display all of their tweets. Since its founding in 2006, Twitter has developed into one of the most widely used social media networks worldwide. Utilizing hashtags to categorise tweets and increase their discoverability by other users is one of Twitter's distinctive features. The pound symbol (#) is used to form hashtags, which are then followed by a word or phrase. It's simple to share and interact with material on Twitter since users may retweet, reply to, and also like other users' tweets. Twitter has developed into a potent tool for exchanging information and facilitating communication, especially during political campaigns and breaking news events. Politicians and journalists frequently use Twitter to disseminate information and interact in real time with their audiences. Twitter has also been used to coordinate social movements and demonstrations, like Black Lives Matter and the Arab Spring. Twitter has still come under fire for its part in disseminating false information and hate speech. The platform has responded to these problems by enacting rules to identify and delete deceptive information and by banning users who breach its terms of service. Despite these initiatives, Twitter still has a difficult