COVID-19 Vaccine Understanding and Aftereffects: Twitter User Mental Health Analysis and Pfizer Stock Predictions for Major Regions

Chaudhry, Deeksha (2021) COVID-19 Vaccine Understanding and Aftereffects: Twitter User Mental Health Analysis and Pfizer Stock Predictions for Major Regions. Masters thesis, Dublin, National College of Ireland.

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Abstract

These discussions can help governments, organizations, and individuals respond to the pandemic. Covid-19 has resulted in unprecedented duration of power outages, loneliness, insecurity, and agony. The impact of Covid-19 is investigated utilizing sentiment analysis and emotion categorization throughout this study. The dataset was constructed by collecting tweets from the last two months in The United Kingdom, The United States, Canada, Singapore, and Ireland. These tweets are then analyzed to determine the mental health of those who use Twitter. Following that, these tweets are utilized to forecast stock prices for the Pfizer corporation, as this is the vaccine is widely used in the aforementioned nations. Various machine learning models were applied and analyzed to get the desired and more accurate results.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning R Medicine > RA Public aspects of medicine > RA790 Mental Health
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	19 Jan 2023 16:51
Last Modified:	06 Mar 2023 13:41
URI:	https://norma.ncirl.ie/id/eprint/6102

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