Impact of COVID-19 on Societal Behavior via Twitter Analytics
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Resumen
The outbreak of the COVID-19 pandemic has caused a notable challenge to the well-being of people all around the globe. In such times, it is of foremost importance to analyze the information posted by people on social media. In this study, a Twitter-based dataset related to COVID-19 has been analyzed, and the effect of the pandemic on societal behavior has been revealed. Tweets have been hydrated and pre-processed using the NLTK toolkit to find the most frequently posted COVID- related words. This research can help identify the social response of people to the Pandemic, realizing what people are majorly concerned about and extracting knowledge about the daily trend of sentiments around the world. It has been concluded from our analysis that rather than the expected negative trend in the use of COVID-19 terms on a daily basis, more positive figurative language has been used in the posted tweets.
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Referencias
15.7 million Mexicans face unemployment during the COVID-19 crisis. (2020, July 24). El Universal. Retrieved from: https://www.eluniversal.com.mx/english/157-million-mexicans-face-unemployment-during-covid-19-crisis
875 people commit suicide during lockdown period in Nepal. (2020, May). Retrieved from http://www.xinhuanet.com/english/2020-05/26/c_139089729.htm
Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M., & Shah, Z. (2020). Top concerns of Tweeters during the COVID-19 pandemic: Infoveillance study. Journal of Medical Internet Research, 22(4), e19016. doi: 10.2196/19016
Alpalhão, M., & Filipe, P. (2020). The Impacts of Isolation Measures Against SARS-CoV-2 Infection on Sexual Health. AIDS and Behavior, 24(8), 2258-2259. doi: 10.1007/s10461-020-02853-x
Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: Modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56, 101475. doi: 10.1016/j.tele.2020.101475
Arinda, S., Patel P. K., & Gaikwad, R. (2020, July 2). Analysis of Suicides Reported Since the Lockdown. The Citizen. Retrieved from: https://www.thecitizen.in/index.php/en/NewsDetail/index/15/18987/Analysis-of-Suicides-Reported-Since-the-Lockdown
Banka, N. (2020, July 12). Explained: The strange case of Turkmenistan, the country with ‘no COVID-19 cases.’ The Indian Express. Retrieved from: https://indianexpress.com/article/explained/turkmenistan-coronavirus-cases-explained-6497242/
Barkur, G., Vibha, & Kamath, G. B. (2020). Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India. Asian Journal of Psychiatry, 51, 102089. doi: 10.1016/j.ajp.2020.102089
Bhat, M., Qadri, M., Beg N.-U.-A., Kundroo, M., Ahanger, N., & Agarwal, B. (2020). Sentiment analysis of Social Media Response on the Covid19 outbreak. Brain, Behavior, and Immunity, 87, 136–137. doi: 10.1016/j.bbi.2020.05.006
Cucinotta, D., & Vanelli, M. (2020). WHO Declares COVID-19 a Pandemic. Acta Biomedica, 91(1), 157-160. doi: 10.23750/abm.v91i1.9397
Department of Global Communications (2020, April 20). 5 ways the UN is fighting ‘infodemic’ of misinformation. United Nations. Retrieved from: https://www.un.org/en/un-coronavirus-communications-team/five-ways-united-nations-fighting-%E2%80%98infodemic%E2%80%99-misinformation
Di Renzo, L., Gualtieri, P., Pivari, F., Soldati, L., Attinà, A., Cinelli, G., … De Lorenzo, A. (2020). Eating habits and lifestyle changes during COVID-19 lockdown: An Italian survey. Journal of Translational Medicine, 18(229), 1-15. doi: 10.1186/s12967-020-02399-5
DocNow/hydrator. (2020). Documenting the Now. [JavaScript]. Retrieved from: https://github.com/DocNow/hydrator (Original work published 2016)
Dubey, A. D. (2020, April 9). Twitter Sentiment Analysis during COVID19 Outbreak. Available at SSRN, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3572023
Eisma, M. C., Boelen, P. A., & Lenferink, L. I. M. (2020). Prolonged grief disorder following the Coronavirus (COVID-19) pandemic. Psychiatry Research, 288, 113031. doi: 10.1016/j.psychres.2020.113031
Fu, K.-W., Liang, H., Saroha, N., Tse, Z. T. H., Ip, P., & Fung, I. C.-H. (2016). How people react to Zika virus outbreaks on Twitter? A computational content analysis. American Journal of Infection Control, 44(12), 1700–1702. doi: 10.1016/j.ajic.2016.04.253
Grieson, J. (2020, July 15). Domestic abuse calls to London police rise by a tenth during lockdown. The Guardian. Retrieved from: https://www.theguardian.com/society/2020/jul/15/domestic-abuse-calls-to-london-police-rise-by-a-tenth-during-lockdown
Hall, B. J., & Tucker, J. D. (2020). Surviving in place: The coronavirus domestic violence syndemic. Asian Journal of Psychiatry, 53, 102179. doi: 10.1016/j.ajp.2020.102179
Hiremath, P., Kowshik, C. S., Manjunath, M., & Shettar, M. (2020). COVID 19: Impact of lock-down on mental health and tips to overcome. Asian Journal of Psychiatry, 51, 102088. doi: 10.1016/j.ajp.2020.102088
IANS (2020, July 7). Suicide cases on the rise in Nepal during COVID-19 lockdown- The New Indian Express. Retrieved from https://www.newindianexpress.com/world/2020/jul/07/suicide-cases-on-the-rise-in-nepal-during-covid-19-lockdown-2166528.html
India Coronavirus: 258090 Cases and 7207 Deaths (n.d.) Retrieved from https://www.worldometers.info/coronavirus/country/india/
Kleinberg, B., van der Vegt, I., & Mozes, M. (2020). Measuring emotions in the COVID-19 real world worry dataset. ArXiv:2004.04225. doi: 10.48550/arXiv.2004.04225
Kraemer, M. U., Yang, C.-H., Gutierrez, B., Wu, C.-H., Klein, B., Pigott, D. M., … Scarpino, S. V. (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science, 368(6490), 493–497. doi: 10.1126/science.abb4218
Lamsal, R. (2020). Corona virus (COVID-19) tweets dataset. IEEE Dataport. doi: 10.21227/781w-ef42
Lamsal, R. (2021). Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence, 51(5), 2790-2804. doi: 10.1007/s10489-020-02029-z
Li, S., Wang, Y., Xue, J., Zhao, N., & Zhu, T. (2020). The impact of COVID-19 epidemic declaration on psychological consequences: A study on active Weibo users. International Journal of Environmental Research and Public Health, 17(6), 2032. doi: 10.3390/ijerph17062032
Liu, I. L., Cheung, C. M., & Lee, M. K. (2010). Understanding Twitter Usage: What Drive People Continue to Tweet. PACIS 2010 Proceedings. 92, Asia.
https://aisel.aisnet.org/pacis2010/92
Mohan M. (2020, June 12). Coronavirus: Domestic violence ’increases globally during lockdown’. BBC News. Retrieved from: https://www.bbc.com/news/av/world-53014211/coronavirus-domestic-violence-increases-globally-during-lockdown
Panwar, H., Gupta, P. K., Siddiqui, M. K., Morales-Menendez, R., Bhardwaj, P., & Singh, V. (2020). A deep learning and grad-CAM based color visualization approach for fast detection of COVID-19 cases using chest X-ray and CT-Scan images. Chaos, Solitons & Fractals, 140, 110190. doi:10.1016/j.chaos.2020.110190
Panwar, H., Gupta, P., Siddiqui, M. K., Morales-Menendez, R., & Singh, V. (2020). Application of Deep Learning for Fast Detection of COVID-19 in X-Rays using nCOVnet. Chaos, Solitons & Fractals, 138, 109944. doi: 10.1016/j.chaos.2020.109944
Pietrobelli, A., Pecoraro, L., Ferruzzi, A., Heo, M., Faith, M., Zoller, T., … Heymsfield, S. B. (2020). Effects of COVID‐19 lockdown on lifestyle behaviors in children with obesity living in Verona, Italy: A longitudinal study. Obesity, 28(8), 1382-1385. doi: 10.1002/oby.22861
Ravilious, K. (2020, May 13). Drop in pollution may bring hotter weather and heavier monsoons. The Guardian. Retrieved from: https://www.theguardian.com/world/2020/may/13/drop-in-pollution-may-bring-hotter-weather-and-heavier-monsoons
Rich, M. (2020, January 30). As Coronavirus Spreads, So Does Anti-Chinese Sentiment. The New York Times. Retrieved from: https://www.nytimes.com/2020/01/30/world/asia/coronavirus-chinese-racism.html
Roshan, R., Feroz, A. S., Rafique, Z., & Virani, N. (2020). Rigorous Hand Hygiene Practices Among Health Care Workers Reduce Hospital-Associated Infections During the COVID-19 Pandemic. Journal of Primary Care & Community Health, 11, 2150132720943331. doi: 10.1177/2150132720943331
Shimizu, K. (2020). 2019-nCoV, fake news, and racism. The Lancet, 395(10225), 685-686. doi: 10.1016/S0140-6736(20)30357-3
Siddiqui, M. K., Morales-Menendez, R., & Ahmad, S. (2020). Application of Receiver Operating Characteristics (ROC) on the Prediction of Obesity. Brazilian Archives of Biology and Technology, 63, e20190736. doi: 10.1590/1678-4324-2020190736
Siddiqui, M. K., Morales-Menendez, R., Gupta, P. K., Iqbal, H., Hussain, F., Khatoon, K., & Ahmad, S. (2020). Correlation between temperature and COVID‑19 (suspected, confirmed and death) cases based on machine learning analysis. Journal of Pure and Applied Microbiology, 14(1), 1017-1024. doi: 10.22207/JPAM.14.SPL1.40
Sohrabi, C., Alsafi, Z., O’Neill, N., Khan, M., Kerwan, A., Al-Jabir, A., Iosifidis, C., & Agha, R. (2020). World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). International Journal of Surgery, 76, 71-76. doi: 10.1016/j.ijsu.2020.02.034
Tanne, J. H., Hayasaki, E., Zastrow, M., Pulla, P., Smith, P., & Rada, A. G. (2020). Covid-19: how doctors and healthcare systems are tackling coronavirus worldwide. BMJ, 368, m1090. doi: 10.1136/bmj.m1090
Van Bavel, J. J., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., …, Willer, R. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour, 4, 460-471. doi: 10.1038/s41562-020-0884-z
Van Der Linden, S., Roozenbeek, J., & Compton, J. (2020). Inoculating against fake news about COVID-19. Frontiers in Psychology, 11, 566790. doi: 10.3389/fpsyg.2020.566790