Paper Title
YouTube Comment Analyzer
Article Identifiers
Authors
Shubham Pareek , Yash Vijay Vargiya , Sudhanshu Agarwal , Laxmikant Vashista
Keywords
Natural language processing (NLP), Sentiment analysis, User-generated content, Text analytics
Abstract
In the contemporary digital landscape, the abundance of user-generated comments on various online platforms presents a formidable challenge for manual analysis. Comment analyzers, leveraging advanced technologies like natural language processing (NLP) and machine learning, offer automated solutions to extract valuable insights from this textual data deluge. This paper aims to explore the significance, functionality, applications, challenges, and ethical considerations of comment analyzers. Through real-world examples and discussions on privacy, bias, and responsible use, this research provides insights into leveraging comment analyzers for informed decision-making and improved user engagement. By synthesizing academic research and industry insights, this paper contributes to a deeper understanding of the role of comment analyzers in shaping digital communication and informs future research and practical implementations in this rapidly evolving field.
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How To Cite
"YouTube Comment Analyzer ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h374-h378, April-2024, Available :https://ijnrd.org/papers/IJNRD2404744.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : h374-h378
Other Publication Details
Paper Reg. ID: IJNRD_219348
Published Paper Id: IJNRD2404744
Downloads: 000121188
Research Area: Science & Technology
Country: JAIPUR, Rajasthan, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404744.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404744
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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