Online platforms such as preprint servers have become an increasingly important way to disseminate new knowledge prior to peer review. While these platforms are accessible to scientists and audiences around the world, there is considerable uncertainty about the reliability of unpublished research, which could lead audiences to assess preprints based on social signals of quality. This study explores how readers allocated attention across preprints in a context of great urgency (the initial months of the COVID-19 pandemic), and the extent to which the scientific community attempted to reduce uncertainty about preprints through endorsements on social media. We find that, conditional on the impact factor of the eventual publication outcome, preprints with authors from Chinese institutions receive less attention, and preprints with USA based authors receive more attention, than preprints with authors from the rest of the world during the early months of the pandemic. We also show that self-organising screening mechanisms such as twitter endorsements drive attention, although these are less common and no more effective for Chinese authored preprints, replicating the original attention gap. The results suggest that location-based biases may persist even on platforms designed to promote unfettered access to early research findings in a context of high urgency and uncertainty.
Megan MacGarvie Megan MacGarvie Megan MacGarvie Megan MacGarvie Megan MacGarvie
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