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Sentiment Analysis Methods to Mitigate Negative Effect of the COVID-19 Pandemic

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dc.contributor.author Mohamud, Sofia A
dc.date.accessioned 2021-02-23T22:00:42Z
dc.date.available 2021-02-23T22:00:42Z
dc.date.issued 2021-01-11
dc.identifier.uri http://hdl.handle.net/1920/11952
dc.description.abstract The goal of this research is to determine crucial factors that played a role in the number of confirmed COVID-19 infections within a given location. We hypothesize that political bias plays a significant role in the rise of COVID-19 cases globally and nationally; specifically, in overriding scientific reasoning for the delay or lack of deploying national policies to address the pandemic. Methods: To determine the validity of our hypothe- sis, we performed a literature review that identified statistical information on 1) the origins of the virus, 2) the lethality of the virus, and 3) potential parties responsible for the creation and release of the virus. In addition to the literature review, our team performed a behavioral analysis using information extracted from social media platforms to identify and determine behavior patterns associated with specific words related to the virus en_US
dc.language.iso en_US en_US
dc.rights Attribution 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by/3.0/us/ *
dc.subject data mining en_US
dc.subject sentiment analysis en_US
dc.subject covid-19 en_US
dc.title Sentiment Analysis Methods to Mitigate Negative Effect of the COVID-19 Pandemic en_US
dc.type Technical Report en_US


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