Promote to protect: data-driven computational model of peer influence for vaccine perception.

ABSTRACT: Vaccine hesitancy and acceptance, driven by social influence, is usually explored by most researchers using exhaustive survey-based studies, which investigate public preferences, fundamental values, beliefs, barriers, and drivers through closed or open-ended questionnaires. Commonly used simple statistical tools do not do justice to the richness of this data. Considering the gradual development of vaccine acceptance in a society driven by multiple local/global factors as a compartmental contagion process, we propose a novel methodology where drivers and barriers of these dynamics are detected from survey participants' responses, instead of heuristic arguments. Applying rigorous natural language processing analysis to the survey responses of participants from India, who are from various soc

SUBMITTER: Ghosh S 

PROVIDER: S-EPMC10764860 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature