Date of Award
2023
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Complex Systems and Data Science
First Advisor
Sarah Nowak
Second Advisor
Chris Danforth
Abstract
Despite national and international organizations such as the CDC and WHO recognizing the value of vaccines and their importance in addressing public health concerns, there has been a decline in coverage for even the most established vaccines over the past three years. The global COVID-19 pandemic has contributed to this decline via decreases in medical resource accessibility and an increase in vaccine hesitancy. Even before the COVID-19 pandemic, WHO had recognized vaccine hesitancy as one of the top ten threats to public health. In the present work, we introduce a background account of (1) vaccine hesitancy and (2) anti-vax activism, along with their potential harms. We then describe how the current methods for studying this pair of trends struggle to capture their turbulent and nuanced nature. Using over 5M messages from BabyCenter, a message board for expecting and new parents, we present methods for identifying a glossary of terms associated with vaccine hesitancy or specific vaccine conversations. By quantifying changes in vocabulary over time and specific to sub-topics our work offers a quantitative starting point for informing targeted strategies to increase vaccination uptake.
Language
en
Number of Pages
50 p.
Recommended Citation
Ward, Carter Willets, "How to analyze parental conversation online: a computational stack for studying vaccine hesitancy." (2023). Graduate College Dissertations and Theses. 1732.
https://scholarworks.uvm.edu/graddis/1732
Included in
Computer Sciences Commons, Public Health Commons, Sociology Commons