The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Coronavirus Pandemic (COVID-19): Emotional Toll Analysis on Twitter
Abstract
People are afraid about COVID-19 and are actively talking about it on social media platforms such as Twitter. People are showing their emotions openly in their tweets on Twitter. It's very important to perform sentiment analysis on these tweets for finding COVID-19's impact on people's lives. Natural language processing, textual processing, computational linguists, and biometrics are applied to perform sentiment analysis to identify and extract the emotions. In this work, sentiment analysis is carried out on a large Twitter dataset of English tweets. Ten emotional themes are investigated. Experimental results show that COVID-19 has spread fear/anxiety, gratitude, happiness and hope, and other mixed emotions among people for different reasons. Specifically, it is observed that positive news from top officials like Trump of chloroquine as cure to COVID-19 has suddenly lowered fear in sentiment, and happiness, gratitude, and hope started to rise. But, once FDA said, chloroquine is not effective cure, fear again started to rise.
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The language of emotions: An analysis of a semantic field
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Dissemination of health information through social networks: Twitter and antibiotics
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Too much Facebook? An exploratory examination of social media fatigue
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Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India
Barkur, G., Vibha, & Kamath, G. B. (2020) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2020.102089 · Cited by 350
The first 2019 novel coronavirus case in Nepal
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Susceptibility to misinformation about COVID-19 around the world
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., & van der Linden, S. (2020) · Royal Society Open Science · doi:10.1098/rsos.201199 · Cited by 1,447
Inoculating Against Fake News About COVID-19
van der Linden, S., Roozenbeek, J., & Compton, J. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.566790 · Cited by 632
Nachega, J. B., Atteh, R., Ihekweazu, C., Sam-Agudu, N. A., Adejumo, P., Nsanzimana, S., Rwagasore, E., Condo, J., Paleker, M., Mahomed, H., et al. (2021) · The American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.21-0033 · Cited by 104
Palacio-Mejía, L. S., Hernández-Ávila, J. E., Hernández-Ávila, M., Dyer-Leal, D., Barranco, A., Quezada-Sánchez, A. D., Alvarez-Aceves, M., Cortés-Alcalá, R., Fernández- Wheatley, J. L., Ordoñez-Hernández, I., et al. (2022) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2022.100303 · Cited by 77
At Least Three Doses of Leading Vaccines Essential for Neutralisation of SARS-CoV-2 Omicron Variant
Singanallur, N. B., van Vuren, P. J., McAuley, A. J., Bruce, M. P., Kuiper, M. J., Gwini, S. M., Riddell, S., Goldie, S., Drew, T. W., Blasdell, K. R., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.883612 · Cited by 15
Metadata
- Authors
- Alowibdi, J. S., Alshdadi, A. A., Daud, A., Dessouky, M. M., & Alhazmi, E. A.
- Venue
- International Journal on Semantic Web and Information Systems
- Publisher
- IGI Global
- Published
- 2021-04
- Volume
- 17
- Issue
- 2
- Pages
- 1-21
- ISSN
- 1552-6283 (ISSN-L)
- 1552-6291
- OpenAlex
- W3153743799
- Cited by
- 1,530
- References
- 16
- FWCI
- 113.98
- Type
- journal article
- Language
- en
- Open access
- closed
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- Alowibdi, J. S., Alshdadi, A. A., Daud, A., Dessouky, M. M., & Alhazmi, E. A. (2021). Coronavirus Pandemic (COVID-19): Emotional Toll Analysis on Twitter. International Journal on Semantic Web and Information Systems. https://doi.org/10.4018/ijswis.2021040101
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