An Efficient CSPK-FCM Explainable Artificial Intelligence Model on COVID-19 Data to Predict the Emotion Using Topic Modeling
Author:
Publisher
Engineering and Technology Publishing
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems,Software
Link
https://www.jait.us/uploadfile/2023/JAIT-V14N6-1390.pdf
Reference35 articles.
1. [1] M. Hung et al., "Social network analysis of COVID-19 Sentiments: Application of artificial intelligence," Journal of Medical Internet Research, vol. 22, no. 8, pp. 113, 2020.
2. [2] A. C Sanders et al., "Unmasking the conversation on masks: Natural language processing for topical sentiment analysis of COVID-19 Twitter discourse," Medrxiv, pp. 110, 2021.
3. [3] R. T. Gandhi, J. B. Lynch, and C. D. Rio, "Mild or moderate COVID-19," New England Journal of Medicine, vol. 383, no. 18, pp. 17571766, 2020.
4. [4] S. Das and A. Dutta, "Characterizing public emotions and sentiments in COVID-19 environment: A case study of India," Journal of Human Behavior in the Social Environment, vol. 31, no. 14, pp. 154167, 2021.
5. [5] X. Y. Song et al., "Classification aware neural topic model for COVID-19 disinformation categorization," PloS One, vol. 16, no. 2, pp. 122, 2021.
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