Alice FLEERACKERS, Scholarly Communications Lab, Simon Fraser University, Canada
Michelle RIEDLINGER, School of Communication, Queensland University of Technology, Australia
Juan Pablo ALPERIN, Scholarly Communications Lab, Simon Fraser University, Canada
Ruhksana AHMED, Department of Communication, University at Albany, State University of New York, United States
The public demand for credible, timely health information during the COVID-19 pandemic has highlighted both the value of digital journalism as a mode of science communication and the challenges journalists face in effectively and accurately conveying evolving health research findings during emergency situations. In the absence of relevant peer-reviewed research, journalistic coverage of COVID-19-related preprints—publicly available research papers that have yet to be peer reviewed—skyrocketed during the pandemic, outstripping media coverage of preprints on other topics.
On one hand, the coverage of this preliminary science can provide timely, relevant insights into prevention and management of COVID-19; on the other hand, the unverified nature of preprint findings, if not clearly communicated, could mislead audiences. The potential for miscommunication is particularly problematic on platforms such as Twitter and Facebook, where content can circulate widely and rapidly, sometimes without appropriate context. This presentation focuses on the digital amplification of uncertain science by examining how online news studies citing media coverage of COVID-19-related preprint research circulate on social media.
To do so, we build on our recently published work tracking the online news media coverage of 100 highly-circulated COVID-19-related preprints. We found that only about half of the media stories mentioning preprints accurately portrayed the research as uncertain or preliminary. Extending this work, the present study applies a mixed method approach to analyze the uptake and circulation of those preprints, and their associated media stories, on Twitter and Facebook. Using data from Altmetric, a company that collects mentions of scholarly documents in online news and social media, we used code (Python scripts) to collect tweet details, Twitter user profiles, and follower relationships of those that engaged with the research. On Facebook, we extract publicly available user data from profiles, groups, and pages of those who post links to the preprint articles or media stories using the social media analytics tool Crowdtangle. We then conducted manual content analyses of social media users’ bios to answer such questions as: Who is posting about COVID-19-related preprints or media stories reporting on them? And what kind of user engagement do these posts receive?
By identifying the online audiences engaging with COVID-19-related preprint research, this study aims to advance understanding of the influence of various digital actors in an increasingly complex, hybrid social media landscape and shed light on an important but understudied topic: communicating the scientific uncertainty of preprint research.