A Machine Learning Approach to Sentiment Analysis of YouTube
Sona Singh
Scholar, Department of Computer Science and Engineering, (AI&ML) , KIPM College of Engineering and Technology, U.P., India
Sonika Bhardwaj
Scholar, Department of Computer Science and Engineering, (AI&ML) , KIPM College of Engineering and Technology, U.P., India
Ranjeet Kumar Dubey
Department of Computer Science and Engineering, (AI&ML) , KIPM College of Engineering and Technology, U.P., India
📌 DOI: https://doi.org/10.63920/tjths.52029
🔑 Keywords: YouTube, social media platforms, Natural Language Processing (NLP), machine learning
📅 Publication Date: 17 April 2026
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This work is licensed under a Creative Commons Attribution 4.0 International License
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Abstract:
IIn the digital age, YouTube has emerged as one of the most influential social media platforms, where users actively share their opinions through comments, likes, and dislikes. These interactions provide valuable insights into public sentiment regarding videos, products, and various topics. However, manually analyzing such a vast volume of user-generated data is both time-consuming and inefficient. To address this challenge, sentiment analysis—also known as opinion mining—offers an automated approach to classify user opinions as positive, negative, or neutral. This study focuses on analyzing YouTube comments using Natural Language Processing (NLP) and machine learning techniques to accurately identify user sentiment. The research involves collecting comment data through the YouTube Data API, followed by preprocessing steps such as data cleaning and normalization to enhance data quality. Feature extraction techniques, including TF-IDF and word embeddings, are applied to capture meaningful textual patterns. Various machine learning models are then developed and trained for effective sentiment classification. Finally, the results are visualized and interpreted to provide clear insights into audience opinions and trends.
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📖 How to Cite
Sona S., Sonika Bhardwaj, Ranjeet Kumar D., (2026). A Machine Learning Approach to Sentiment Analysis of YouTube. TEJAS J. Technol. Humanit. Sci.,, Vol. 05, Issue 02. https://doi.org/10.63920/tjths.52029
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