Year: 2025
Type: article
Abstract: : This paper details the implementation of a system for performing sentiment analysis on YouTube comments. With the vast amount of user-generated content on YouTube, understanding the sentiment expressed in comments is crucial for content creators, marketers, and researchers. This paper covers the process of data collection, preprocessing, sentiment analysis model selection, training, evaluation, and potential applications. We explore various Natural Language Processing (NLP) techniques and machine learning models, providing a comprehensive guide to building an effective sentiment analysis system for YouTube comments. The system utilizes the YouTube Data API to download video comments and employs advanced NLP techniques to classify comments into positive, negative, and neutral sentiment classes. The application delivers actionable insights, enabling content creators to track audience engagement, identify trends, and make data-driven decisions.
DOI: 10.55041/ijsrem45687
Author: Sandesh Srivastav
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409772483