Does Discussion Matter? Interaction Dynamics in Transparent Peer Review
Shiyao WeiRan Bi
Sep 2026
Human-computer Interaction
Abstract
Open peer review is advocated as a way to make review more dialogic, yet evidence on whether it changes participant behavior remains scarce. We compare two transparent review designs: Nature Human Behaviour, an editor-mediated model, and International Conference on Learning Representations 2023, a discussion-based model. Treating cross-mentions, moments when one participant explicitly names another beyond the immediate dyad, as the analytic unit, we combine social network analysis of 56 NHB articles and 371 ICLR notable papers with qualitative coding grounded in Knowledge Building theory. Structurally, NHB forms hub-and-spoke networks with zero reviewer-to-reviewer reciprocity, whereas ICLR forms partial-mesh networks with significantly more direct cross-referencing. Functionally, the distribution of communicative functions is similar across venues, but who performs them differs: editors aggregate at NHB, while authors and reviewers absorb that labor at ICLR. The designs differ most in how communicative labor is distributed across roles, suggesting platforms should support it as explicit, built-in functions.
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