Extracting Sentiments from Youtube Comments Using Deep Learning and Transformers

Abstract

Abstract: YouTube is the most used social media platform, and it has been the most popular website where users can post the video. The public generally does comment, like or dislike, video-sharing on a YouTube video. Comment plays a vital role in expressing opinions and mindset, and it is used as an expression of public opinion. The massive amount of comment is generated mainly on famous channels where challenges arise to analyse public opinion or behaviour regarding that particular video. This project proposes sentiment analysis on YouTube video by Natural Language Processing (NLP) technique along with Deep Learning techniques Recurrent Neural Network (RNN) and Gated Recurrent Unit (GRU) models. Sentiment analysis is when comprehension, citation, and processing of text-based data is done, and it directly converts it into sentiment information. This analysis help users to get the report of their YouTube video. The output of this analysis gives the classification of sentiment analysis, as Positive, negative, or neutral.