Abstract

Abstract Partisanship played a key role in shaping individuals’ responses to the COVID-19 pandemic in the United States. The current project applies the extended parallel processing model (EPPM) to examine how the content features of White House press conferences were associated with the partisan gap in perceptions and behavior during the early stage of the pandemic. Using supervised machine learning, Study 1 analyzes the White House press conferences regarding the pandemic during 2020. The results demonstrate that the White House focused on efficacy but included minimal threat information. Study 2 uses the threat and efficacy information in White House press conferences to predict perceived threat and efficacy as well as self-quarantine behavior measured by longitudinal surveys using nationally representative samples of U.S. adults. Time-series analysis shows that an increase of threat information from the White House was associated with a subsequent decrease in the partisan gap between Democrats and Republicans on perceived threat and self-quarantine behavior by increasing perceived threat and self-quarantine behavior among Republicans. This study contributes to presidential communication research by systematically examining specific message features and linking them to public perceptions and behaviors in the context of a public health crisis. The study also extends the EPPM to a dynamic model, estimating the asymmetric effects and self-continuity of positive (i.e., efficacy) and negative (i.e., threat) information on perceptions and behaviors.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call