Enhanced sentiment analysis regarding COVID-19 news from global channels
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Transportation
Link
https://link.springer.com/content/pdf/10.1007/s42001-022-00189-1.pdf
Reference70 articles.
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3. Ahmad, W., Wang, B., Han, Xu., Minghua, Xu., & Zeng, Z. (2021). Topics, sentiments, and emotions triggered by COVID-19-related tweets from iran and turkey official news agencies. SN Computer Science, 2(5), 1–19.
4. Alam, K. N., Khan, M. S., Dhruba, A. R., Khan, M. M., Al-Amri, J. F., Masud, M., & Rawashdeh, M. (2021). Deep learning-based sentiment analysis of COVID-19 vaccination responses from twitter data. Computational and Mathematical Methods in Medicine, 2021.
5. Aljabri, M., Chrouf, S. M., Alzahrani, N. A., Alghamdi, L., Alfehaid, R., Alqarawi, R., Alhuthayfi, J., Alduhailan, N., et al. (2021). Sentiment analysis of Arabic tweets regarding distance learning in Saudi Arabia during the COVID-19 pandemic. Sensors, 21(16), 5431.
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