Sentiment Patterns in YouTube Comments: A Comprehensive Analysis

The sentiment analysis system is developed for YouTube comments, capable of accurately categorizing comments into positive, negative, or neutral sentiments. The system effectively handles challenges such as informal language, slang, and diverse topics, while being scalable and adaptable to different content genres. The objective is to provide a valuable tool for content creators, marketers, and researchers to gain insights into audience sentiments on YouTube, facilitating data driven decision-making and enhancing user engagement strategies.

Authors

Publication Details

Journal
Computer Science & Engineering An International Journal
Published
2025-03-28
DOI
https://doi.org/10.5121/cseij.2025.15119
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Sentiment Patterns in YouTube Comments: A Comprehensive Analysis

Saritha Shetty, Savitha Shetty, Deepthi Shetty, Priya Kamath B
Computer Science & Engineering An International Journal
Sentiment Analysis and Opinion Mining
article

Sentiment Patterns in YouTube Comments: A Comprehensive Analysis

Saritha Shetty, Savitha Shetty, Deepthi Shetty, Priya Kamath B
article en

Abstract

The sentiment analysis system is developed for YouTube comments, capable of accurately categorizing comments into positive, negative, or neutral sentiments. The system effectively handles challenges such as informal language, slang, and diverse topics, while being scalable and adaptable to different content genres. The objective is to provide a valuable tool for content creators, marketers, and researchers to gain insights into audience sentiments on YouTube, facilitating data driven decision-making and enhancing user engagement strategies.

Computer Science & Engineering An International JournalVol. 15(1)
Openalex Percentile: Top 97%
Sentiment Analysis and Opinion Mining
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