Predicting zip code-level vaccine hesitancy in US Metropolitan Areas using machine learning models on public tweets.

ABSTRACT: Although the recent rise and uptake of COVID-19 vaccines in the United States has been encouraging, there continues to be significant vaccine hesitancy in various geographic and demographic clusters of the adult population. Surveys, such as the one conducted by Gallup over the past year, can be useful in determining vaccine hesitancy, but can be expensive to conduct and do not provide real-time data. At the same time, the advent of social media suggests that it may be possible to get vaccine hesitancy signals at an aggregate level, such as at the level of zip codes. Theoretically, machine learning models can be learned using socioeconomic (and other) features from publicly available sources. Experimentally, it remains an open question whether such an endeavor is feasible, and how it would

SUBMITTER: Melotte S 

PROVIDER: S-EPMC9931269 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature