Sentiment Analysis Methods to Mitigate Negative Effect of the COVID-19 Pandemic
| 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.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 | |
| dc.identifier.uri | https://hdl.handle.net/1920/11952 | |
| dc.language.iso | en_US | |
| dc.rights | Attribution 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by/3.0/us/ | |
| dc.subject | Data mining | |
| dc.subject | Sentiment analysis | |
| dc.subject | COVID-19 | |
| dc.title | Sentiment Analysis Methods to Mitigate Negative Effect of the COVID-19 Pandemic | |
| dc.type | Technical Report |