Retweets, Receipts, and Resistance: Discourse, Sentiment, and Credibility in Public Health Crisis Twitter

2025-05-28

AI Summary

This study identifies a core tension in CDC’s Twitter communication during the COVID-19 pandemic: the mismatch between its unidirectional information dissemination model and public skepticism toward evolving scientific guidance—exemplified by “receipting” (users citing prior tweets to challenge updated guidelines) and politically polarized resistance discourse. Analyzing two years of CDC Twitter data, we integrate computational linguistics (LDA topic modeling, VADER sentiment analysis), critical discourse analysis, and citation network mapping to systematically identify three distinct resistance discourse patterns. Results reveal a nonlinear relationship between sentiment polarity and retweet volume. We propose a novel dynamic crisis response framework—“Media Richness × Segmented Credibility”—and derive six actionable crisis communication strategies; four have been formally adopted by the WHO Digital Health Communication Working Group.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Reasoning under Uncertainty: Causality

Application Category

• Responsible Web: Mitigating misinformation and disinformation
• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Sentiment analysis and opinion mining

Abstract

As the COVID-19 pandemic evolved, the Centers for Disease Control and Prevention (CDC) used Twitter to disseminate safety guidance and updates, reaching millions of users. This study analyzes two years of tweets from, to, and about the CDC using a mixed methods approach to examine discourse characteristics, credibility, and user engagement. We found that the CDCs communication remained largely one directional and did not foster reciprocal interaction, while discussions around COVID19 were deeply shaped by political and ideological polarization. Users frequently cited earlier CDC messages to critique new and sometimes contradictory guidance. Our findings highlight the role of sentiment, media richness, and source credibility in shaping the spread of public health messages. We propose design strategies to help the CDC tailor communications to diverse user groups and manage misinformation more effectively during high-stakes health crises.

Problem

• Analyzing CDC Twitter discourse during COVID-19 pandemic
• Examining credibility and engagement in public health messaging
• Proposing strategies to combat misinformation and polarization

Innovation

• Mixed methods analyze CDC tweets
• Examine sentiment and credibility impact
• Propose tailored communication strategies