Classifiers for Sentiment Analysis of YouTube Comments: A Comparative Study

Exponential increase in online textual information in recent years has led to enhanced interest in applying machine learning (ML) and natural language processing (NLP) to the analysis of text. Sentiment analysis tries to identify, extract, quantify, and study emotional content and subjective information by the application of natural languages processing , computational analysis of text , biometrics, and computational linguistics . Sentiment analysis and use of classifiers on YouTube comments are the most researched topic nowadays. As the count of dislikes on YouTube videos are hidden, it becomes relevant to try and classify YouTube comments using techniques of sentiment analysis into positive, negative, or neutral. This study mainly focuses on comparison of classifiers used to classify YouTube comments.