Monitoring the emotional response to the COVID-19 pandemic using sentiment analysis: a case study in Mexico

dc.contributor.affiliationhttps://ror.org/03ayjn504es_MX
dc.contributor.affiliationInstituto Tecnológico y de Estudios Superiores de Monterreyes_MX
dc.contributor.authorLeón Sandoval, Edgar
dc.contributor.authorZareei, Mahdi
dc.contributor.authorBarbosa Santillán, Liliana Ibeth
dc.contributor.authorFalcón Morales, Luis Eduardo
dc.contributor.authorPareja Lora, Antonio
dc.contributor.authorOchoa Ruiz, Gilberto
dc.contributor.editorHošovský, Alexander
dc.date.accessioned2023-07-11T22:23:59Z
dc.date.available2023-07-11T22:23:59Z
dc.date.issued2022-05-18
dc.description.abstractThe world is facing the COVID-19 pandemic, leading to an unprecedented change in the lifestyle routines of millions. Beyond the general physical health, financial, and social repercussions of the pandemic, the adopted mitigation measures also present significant challenges in the population’s mental health and health programs. It is complex for public organizations to measure the population’s mental health in order to incorporate it into their own decision-making process. Traditional survey methods are time-consuming, expensive, and fail to provide the continuous information needed to respond to the rapidly evolving effects of governmental policies on the population’s mental health. A significant portion of the population has turned to social media to express the details of their daily life, rendering this public data a rich field for understanding emotional and mental well-being. This study aims to track and measure the sentiment changes of the Mexican population in response to the COVID-19 pandemic. To this end, we analyzed 760,064,879 public domain tweets collected from a public access repository to examine the collective shifts in the general mood about the pandemic evolution, news cycles, and governmental policies using open sentiment analysis tools. Sentiment analysis polarity scores, which oscillate around -0.15, show a weekly seasonality according to Twitter’s usage and a consistently negative outlook from the population. It also remarks on the increased controversy after the governmental decision to terminate the lockdown and the celebrated holidays, which encouraged the people to incur social gatherings. These findings expose the adverse emotional effects of the ongoing pandemic while showing an increase in social media usage rates of 2.38 times, which users employ as a coping mechanism to mitigate the feelings of isolation related to long-term social distancing. The findings have important implications in the mental health infrastructure for ongoing mitigation efforts and feedback on the perception of policies and other measures. The overall trend of the sentiment polarity is 0.0001110643.es_MX
dc.format.mediumTextoes_MX
dc.identificator7||33es_MX
dc.identifier.citationLeón-Sandoval, E., Zareei, M., Barbosa-Santillán, L. I., Falcón Morales, L. E., Pareja Lora, A., & Ochoa Ruiz, G. (2022). Monitoring the emotional response to the COVID-19 pandemic using sentiment analysis: A case study in Mexico. Computational Intelligence and Neuroscience, 2022, 1–11. https://doi.org/10.1155/2022/4914665es_MX
dc.identifier.cvu1006856es_MX
dc.identifier.doihttps://doi.org/10.1155/2022/4914665
dc.identifier.issn1687-5265
dc.identifier.journalComputational Intelligence and Neurosciencees_MX
dc.identifier.orcidhttps://orcid.org/0000-0002-2904-327Xes_MX
dc.identifier.orcidhttps://orcid.org/0000-0001-6623-1758es_MX
dc.identifier.orcidhttps://orcid.org/0000-0002-3509-9667es_MX
dc.identifier.orcidhttps://orcid.org/0000-0001-5804-4119es_MX
dc.identifier.orcidhttps://orcid.org/0000-0002-9896-8727es_MX
dc.identifier.scopusid57204466836es_MX
dc.identifier.urihttps://hdl.handle.net/11285/651011
dc.identifier.volume2022es_MX
dc.language.isoenges_MX
dc.publisherHindawies_MX
dc.relation.isFormatOfpublishedVersiones_MX
dc.relation.urlhttps://www.hindawi.com/journals/cin/2022/4914665/es_MX
dc.rightsopenAccesses_MX
dc.rights.urihttp://creativecommons.org/licenses/by/4.0es_MX
dc.subjectINGENIERÍA Y TECNOLOGÍA::CIENCIAS TECNOLÓGICASes_MX
dc.subject.countryEstados Unidos de América / United Stateses_MX
dc.subject.keywordCOVID-19es_MX
dc.subject.keywordsentiment analysises_MX
dc.subject.keywordTwitteres_MX
dc.subject.keywordIngenierías y Desarrollo Tecnológicoes_MX
dc.subject.lcshTechnologyes_MX
dc.titleMonitoring the emotional response to the COVID-19 pandemic using sentiment analysis: a case study in Mexicoes_MX
dc.typeArtículo

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