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

Keywords:
Sentiment analysis Computer science Data science Information retrieval Natural language processing

Metrics

32
Cited By
13.41
FWCI (Field Weighted Citation Impact)
5
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Digital Marketing and Social Media
Social Sciences →  Social Sciences →  Sociology and Political Science

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