Unveiling Emotions in the Digital Arena: Sentiment Analysis of YouTube Comments on FIFA World Cup 2022

YouTube is a popular video sharing website and a social networking platform where users can upload (only registered users), watch and share videos on any particular topic with anyone who can access the site and also share their views about the video in the comment section. Since the YouTube comment section has no word/character limit, the users/viewers can easily express their thoughts and viewpoint in great detail. Also, in the comment section, the users make use of all kinds of emoticons, abbreviations, images, GIFs, etc. In this paper, we deploy different machine learning algorithm along with the Tf-IDF (term frequency- inverse document frequency) method on the comments collected from various YouTube videos on the FIFA World Cup 2022 and compute an accuracy of 81.81% with Random Foresta and 83.03% with Logistic Regression