Date of Completion

2021

Document Type

Honors College Thesis

Department

Mathematics & Statistics

Thesis Type

Honors College

First Advisor

Sheila Weaver

Keywords

Twitter, word frequency, coronavirus, humor, machine learning, survey

Abstract

Using humor as a means of deflecting from stress or anxiety is a widely-occurring practice and takes many different forms, well documented in studies of first-responders or emergency service personnel, for example. This paper attempts to quantify this phenomenon in light of the COVID-19 pandemic by analyzing a large body of Tweets between March and June 2020. In the paper, different methods are used to categorize pieces of text and determine whether humor as a form of personal resiliency occurs on social media, how common this is, and how it manifests itself. The paper also analyzes an original survey administered to around 200 respondents to explore more specifically how individuals use humor to respond to stress, particularly dark humor, and what Covid-related topics were sources of humor.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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