Ch. Kesava Manikanta, A. Gowtham, Ch. Prasanth Kumar, Ch. Sai Sundhar Raghuram, B. Sai Mahesh, B. Sai Jyothi
Department of Information Technology, Vasireddy Venkatadri Institute of Technology, Guntur, India.
Analyzing comments on YouTube may yield invaluable insights on the demographics, hobbies, and preferences of the viewership. By looking into comment patterns, we may identify recurring themes, intriguing topics, and even potential collaborations. We may group comments using natural language processing techniques into three categories: good, negative, and neutral. This research helps identify key trends, gauge viewer sentiment, and assess how well a video is received overall. Material providers may use the information gathered from comments to better tailor their material to the specific needs and tastes of their audience, which will ultimately boost viewer satisfaction and engagement.
Keywords: Machine learning, Bidirectional Encoder Representation from Transformers (BERT), YouTube comments, Transformers.
Journal Name :
EPRA International Journal of Research & Development (IJRD)

Published on : 2023-11-06

Vol : 8
Issue : 11
Month : November
Year : 2023
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