YouTube Video Analyzer Using Sentiment Analysis

Authors

  • Goli Sushma Assistant Professor, Department of CSE (Data Science), Gurunanak institutions Technical Campus, Hyderabad
  • Vadicherla Raju Assistant Professor , Department of CSE(Data Science), Vignana Bharathi Institute of Technology, Hyderabad, India
  • Rajashekar Kandakatla Assistant Professor, Department of CSE ( Artificial Intelligence and Machine Learning), Vaagdevi College of Engineering(Autonomous), Bollikunta, Warangal, Telangana
  • Neethipudi Sashi Prabha Assistant Professor , Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Technology, Hyderabad
  • Rajesh Saturi Associate Professor Department of Computer Science and Engineering, Vignana Bharathi Institute of Technology, Hyderabad, India
  • L. Mohan Associate Professor, Dept. CSE(Internet of Things), Balaji Institute of Technology and Science(Autonomous), Narsampeta, Warangal, Telangana

Keywords:

Sentiment analysis, Natural Language Processing, Opinion extraction, Decision–making

Abstract

Sentiment analysis is a method used to ascertain the opinions and viewpoints of people regarding any service or product. With millions of views, YouTube is one of the most widely used sites for sharing videos. With the ever-increasing popularity of online videos and the exponential growth of user-generated content, understanding the quality and relevancy of content has become crucial for viewers by looking over the comments, number of views, and number of likes manually. The goal of this paper is to create a thorough methodology and a useful tool for assessing user sentiment on YouTube videos. The suggested method extracts text comments and transcripts from YouTube videos for examination using cutting-edge natural language processing algorithms and categorizes them into opinions that are neutral, positive, negative, relevant, and irrelevant along with a transcript summary. Ultimately, this research endeavors to revolutionize the way YouTube videos are analyzed, facilitating informed decision-making and enhancing user experience on the platform.

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References

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https://ieeexplore.ieee.org/document/9396049

https://www.sciencedirect.com/science/article/pii/S1877050920323553

https://www.isroset.org/pdf_paper_view.php?paper_id=2461&6-ISROSET-IJSRCSE- 06279.pdf

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Published

23.02.2024

How to Cite

Sushma, G. ., Raju, V. ., Kandakatla, R. ., Prabha, N. S. ., Saturi, R. ., & Mohan, L. . (2024). YouTube Video Analyzer Using Sentiment Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 597–601. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/4897

Issue

Vol. 12 No. 16s (2024)

Section

Research Article

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