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Public health crises—from the HIV/AIDS epidemic to the COVID-19 pandemic—place enormous pressure on public health organizations to communicate timely, accurate, and consistent information to the public. Yet when organizations contradict themselves over time, they may inadvertently fuel the very misinformation they seek to combat. This paper develops a theory of misinformation-sharing, conceptualizing perceived contradictions in organizational messaging as discursive opportunity structures that enable distrusting actors to spread misinformation during moments of acute crisis. Using an original corpus of over 43,500 COVID-19-relevant tweets from 48 American federal and state public health organizations and nearly 200,000 quote-tweets of those posts, we model within-organization message inconsistencies as longitudinal contradiction networks using a novel combination of biterm topic modeling, large language model classification, and social network methods. Dyadic regressions and exponential random graph models test whether organizational tweets involved in contradiction dyads attract higher rates of misinformation-sharing. We further hypothesize that crisis severity (measured by state COVID case rates) amplifies this effect, particularly within more politically conservative contexts. Findings will advance scholarship on organizational crisis communication and the conditions under which institutional inconsistency undermines public trust during emergencies.
Marshall A. Taylor, New Mexico State University
Heather Harper, New Mexico State University
Jagdish Khubchandani, New Mexico State University
Sanuj Kumar, New Mexico State University
Sumanth Reddy Nandhikonda, New Mexico State University
Luke Burks, New Mexico State University
Saba Omidian, New Mexico State University