COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations

Please cite the following paper when using this dataset:Vanessa Su and Nirmalya Thakur, “COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations”, Proceedings of the IEEE 15th Annual Computing and Communication Workshop and Conference 2025, Las Vegas, USA, Jan 06-08, 2025.This dataset contains data of YouTube videos about COVID-19 from January 2023 to October 2024. For each video, the video URL, video ID, video title, video description, date of publication, number of likes, number of views, the duration (in seconds), language, tags, categories, and availability of captions, are presented as separate attributes in the dataset.