Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media

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The COVID-19 pandemic highlighted the importance of vaccines as the most effective defense against the virus, yet vaccine hesitancy remains a pressing public health challenge, especially with emerging variants. This study explores the potential of social media data as a complementary source to traditional surveys for predicting vaccine hesitancy in the ten largest U.S. metropolitan areas, using machine learning models that integrate social, demographic, and economic variables. Results show that models incorporating social media or survey data, particularly with the XGBoost algorithm, outperform baseline models, emphasizing the promise of social media data, the variability of influential factors across communities, and the need for tailored, data-driven interventions.

Recommended citation: Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media. K Sasse, R Mahabir, O Gkountouna, A Crooks, A Croitoru - PLOS ONE, 2024.