He Wang, Yang Ouyang, Yuchen Wu, Chang Jiang, Lixia Jin, Yuanwu Cao, Quan Li
KMTLabeler: An Interactive Knowledge-Assisted Labeling Tool for Medical Text Classification
IEEE transactions on visualization and computer graphics
article presents causal inference analysis vaccine hesitancy coronavirus disease 2019 covid19 vaccines based sociodemographic data obtained via questionnaires applied sample brazilian population data includes respondents political preferences age group education salary range country region sex believing fake news vaccine confidence intention get covid19 vaccine research created causal graph using variables seeking answer questions probability people getting vaccinated results research corroborate findings observed literature also presenting unique findings perception vaccine safe positively affected age group negatively religion ii older person greater probability considering vaccine safe consequently getting vaccinated iii religion variable showed great importance model since simultaneous causal effect political preferences perception vaccine safety iv data reveal probability person accepting vaccination covid19 reduced given fact believe fake news related vaccine methodology applied research replicated populations countries possible generate customized models general causal models helpful agencies dealing vaccine hesitancy decide variables addressed reduce phenomenon