Date of Award

2019

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematical Sciences

First Advisor

Chris M. Danforth

Second Advisor

Peter S. Dodds

Abstract

Globally, the 2019 Coronavirus pandemic (COVID-19) impacted and threatened the everyday lives and wellbeing of humanity. The development of a vaccine resulted in widespread discourse on social media platforms like Twitter, leading to potentially divergent sentiments about the COVID-19 vaccine. Given the novelty and polarity of vaccine sentiment and discourse, critical knowledge gaps exist as to how these factors develop. This study aims to characterize rapidly growing vaccine-specific dis- course by identifying words and phrases connected to the anchor 1-gram "vaccin*", the derivative of "vaccination" and "vaccinate", amongst others. This study draws from a collection of social media posts on Twitter ("tweets") extracted from a data stream of approximately 10 percent of all English tweets for the past ten years. To characterize vaccine discourse, we examine discourse patterns surrounding specific to standout events over the duration of the Coronavirus pandemic. Within the timeframe of 2019-2021, we found total vaccine discourse increased by several orders of magnitude relative to the average of the ten years of Twitter data. Patterns of increased discourse correspond with political announcements including the Center for Disease Control and presidential announcements of COVID-19. Other events of interest include advances in the scientific community’s development of a vaccine notably indicating approval in March 2020 in tandem with vaccine implementation programs in the United States. While the overall ambient happiness plummets within the early Spring 2020 peak of COVID-19, our results show that ambient happiness related to vaccine discourse remains relatively stable. In contrast, the lexicon of words surrounding vaccine discourse change from anticipatory discourse referencing past Measles Mumps and Rubella (MMR) vaccines to reactionary discourse as the vaccines distribution occurs. Similarly, phrases used to previously describe anti-vaccination sentiment develop new archetypes of vaccine hesitancy. Overall, this study demonstrates that the sheer magnitude of amplified discourse is further characterized by the type of event and the subject, scientific or political communities disseminating information.

Language

en

Number of Pages

48 p.

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Mathematics Commons

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