Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework

Drawing upon the social amplification of risk (SARF) and the issue-attention cycle framework, we examined the amplification of COVID-19 risk-related tweets through (a) topics: key interests of discussion; (b) temperament: emotions of tweets; (c) topography (i.e., location); and (d) temporality (i.e., over time). We computationally analyzed 1,641,273 tweets, and conducted manual content analysis on a subset of 6,000 tweets to identify how topics, temperament, and topography of COVID-19 tweets were associated with risk amplification - retweet and favorite count - using negative binomial regression. We found 11 dominant COVID-19 topics-health impact, economic impact, reports of lockdowns, report of new cases, the need to stay home, coping with COVID-19, news about President Trump, government support, fight with COVID-19 by non-government entities, origins, and preventive measure in our corpus of tweets across the issue-attention cycle. The negative binomial regression results showed that at the pre-problem stage, topics on President Trump, speculation of origins, and initiatives to fight COVID-19 by non-government entities were most likely to be amplified, underscoring the inherent politicization of COVID-19 and erosion of trust in governments from the start of the pandemic. We also found that while tweets with negative emotions were consistently amplified throughout the issue-attention cycle, surprisingly tweets with positive emotions were amplified during the height of the pandemic - this counter-intuitive finding indicated signs of premature and misplaced optimism. Finally, our results showed that the locations of COVID-19 tweet amplification corresponded to the shifting COVID-19 hotspots across different continents across the issue-attention cycle. Theoretical and practical implications of risk amplification on social media are discussed.