Information Retrieval
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 (Paper accepted for publication, Preprint: https://arxiv.org/abs/2412.17180).
Abstract:
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Please cite the following paper when using this dataset:
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To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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This dataset is hosted on IEEE DataPort(TM), a data repository created by IEEE to facilitate research reproducibility. A Systematic Literature Review SLR is presented on information retrieval for IoT and WoT scenarios, containing the definition of the research questions and the selection strategy. We specify the inclusion and exclusion criteria in conjunction with the quality assurance criteria. The data extraction procedure is then outlined.
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<p>Features of each news according to seven credibility categories</p>
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