Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study
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DOI: 10.1007/s10796-021-10152-6
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- Nafei Zhu & Baocun Chen & Siyu Wang & Da Teng & Jingsha He, 2022. "Ontology-Based Approach for the Measurement of Privacy Disclosure," Information Systems Frontiers, Springer, vol. 24(5), pages 1689-1707, October.
- Mohammad Alamgir Hossain & Md. Maruf Hossan Chowdhury & Ilias O. Pappas & Bhimaraya Metri & Laurie Hughes & Yogesh K. Dwivedi, 2023. "Fake news on Facebook and their impact on supply chain disruption during COVID-19," Annals of Operations Research, Springer, vol. 327(2), pages 683-711, August.
- Yang, Zaoli & Wu, Qingyang & Venkatachalam, K. & Li, Yuchen & Xu, Bing & Trojovský, Pavel, 2022. "Topic identification and sentiment trends in Weibo and WeChat content related to intellectual property in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
- Paras Bhatt & Naga Vemprala & Rohit Valecha & Govind Hariharan & H. Raghav Rao, 2023. "User Privacy, Surveillance and Public Health during COVID-19 – An Examination of Twitterverse," Information Systems Frontiers, Springer, vol. 25(5), pages 1667-1682, October.
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Keywords
Twitter; Emotion analysis; Deep learning; COVID’19; Transfer learning; RoBERTa;All these keywords.
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