A Renewed Perspective on Sentiment Analysis of YouTube Comments for Unlocking Viewer Emotions

Abstract

In today's social media-driven world, understanding public sentiment is crucial for creators and brands. The research presents a new method of sentiment analysis to decode the collective sentiment. By having YouTube commentator posts, a bottom-up approach that is elaborate and intended to evaluate audience. interactive and brand perception. The paper utilizes a set of YouTube comments as one of the datasets. have access to a variety of trending videos of different genres. Preprocessing of the data is done to eliminate noise and clean up the text to be analyzed. The process will entail the use of TextBlob Sentiment Analyzer. when it comes to sentiment classification, the division of sentiment into positive, neutral and negative ones. Also, there are sophisticated methods, such as analysis of emojis, in order to estimate emotional undertones and Word Cloud visualizations are produced in order to depict the most salient sentiment-related. words. The results of the research provide useful information on popular topics and interest among the audience. levels, which may make content strategy and brand marketing choices. The outcome of the scaling shows the main trends in the sentiments of the viewers and accuracy was 96.3. These insights empower creators and brands to optimize their content, respond to audience issues and, finally, improve their Internet image and presence. This study highlights the significance of sentiment analysis in the comprehension and reaction towards the societal perception in the changing area of social media.