login
Home / Papers / Youtube Comments Sentiment Analysis

Youtube Comments Sentiment Analysis

15 Citations•2024•
Rushikesh Giri, Mihir Sirsath, Harshil T. Kanakia
2024 IEEE 9th International Conference for Convergence in Technology (I2CT)

This study classifies YouTube comments, investigates sentiment analysis techniques that can be used on them, and offers insightful information useful for data mining and sentiment analysis research.

Abstract

Sentiment analysis is a method used to identify and understand user opinions and viewpoints regarding a product or service. YouTube, one of the most popular video-sharing platforms, garners millions of views daily, resulting in a plethora of user comments that hold valuable information for improving video rankings. To extract sentiment from these comments, Machine learning techniques and natural language processing (NLP) are used.. Various attempts have been made to classify sentiment into two (positive or negative), three (positive, negative, and neutral), or multiple (e.g., happy, surprised, sad, angry) classes. This study classifies YouTube comments, investigates sentiment analysis techniques that can be used on them, and offers insightful information useful for data mining and sentiment analysis research