Sentiment Analysis of COVID-19 Lockdown in India
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7862-5_35
Reference19 articles.
1. Drias, H., & Drias, Y. (2020). Mining Twitter data on COVID-19 for sentiment analysis and frequent patterns discovery. medRxiv, May 2020. https://doi.org/10.1101/2020.05.08.20090464
2. Prakruthi, V., Sindhu, D., & Anupama Kumar, S. (2018). Real time sentiment analysis of Twitter posts. In 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS). IEEE.
3. Manguri, K.H., Ramadhan, R. N., & Amin, P. M. (2020). Twitter sentiment analysis on worldwide COVID-19 outbreaks. Kurdistan Journal of Applied Research (KJAR). https://doi.org/10.24017/covid.8
4. Singh, M., Jakhar, A. K., & Pandey, S. (2021). Sentiment analysis on the impact of coronavirus in social life using the BERT model. Social Network Analysis and Mining, 11(1), 33.
5. Jain, Y., & Tirth, V. (2020). Sentiment analysis of tweets and texts using python on stocks and COVID-19. International Journal of Computational Intelligence Research, 16(2), 87–104.
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