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Social Media Video 2024 Outbreak of Measles Sentiment Analysis Dataset

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During virus outbreaks of the recent past, videos on social media platforms played a crucial role in keeping the global population informed and updated regarding various aspects of the outbreaks. As a result in the last few years, researchers from different disciplines have focused on the development of datasets of videos published on YouTube, TikTok, and similar websites. No prior work in this field has focused on the development of a dataset of videos about the ongoing outbreak of measles, published on social media platforms.

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Description

These websites primarily include YouTube and TikTok, which account for 48.6% and 15.2% of the videos, respectively. The remainder of the websites include Instagram and Facebook as well as the websites of various global and local news organizations. For each of these videos, the URL of the video, title of the post, description of the post, and the date of publication of the video are presented as separate attributes in the dataset. After developing this dataset, sentiment analysis (using VADER), subjectivity analysis (using TextBlob), and fine-grain sentiment analysis (using DistilRoBERTa-base) of the video titles and video descriptions were performed.

 

Please cite the following paper when using this dataset:

N. Thakur, V. Su, M. Shao, K. Patel, H. Jeong, V. Knieling, and A.Bian “A labelled dataset for sentiment analysis of videos on YouTube, TikTok, and other sources about the 2024 outbreak of measles,” Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, USA, 29 June – 4 July 2024. (URL: https://dl.acm.org/doi/10.1007/978-3-031-76806-4_17)

 

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