Trust-Aware Feed Ranking for Scholarly Collaboration Networks
We study how follow edges, review quality, graph proximity and freshness can be blended into an explainable feed optimized for high-signal research discovery.
Collection workspace
Reading path for trust signals, review quality, moderation and feed ranking in research products.
Collection state
Use this page as the stable reading surface, then switch to graph when the relationships between items need to become visible.
Next routes
Highlight works
We study how follow edges, review quality, graph proximity and freshness can be blended into an explainable feed optimized for high-signal research discovery.
We evaluate rubric design for structured reviews, moderation queues and reviewer calibration in technical communities.
We propose ledger-based moderation records that improve accountability, appeals and policy learning in research products.
Curated items
We study how follow edges, review quality, graph proximity and freshness can be blended into an explainable feed optimized for high-signal research discovery.
Useful bridge between trust, ranking and collaboration intent.
Studies trust signals and structured peer feedback in online science.
Author node worth tracking for trust and peer-feedback work.
Signals, incentives and matching for scholarly collaboration.
Topic anchor for the full trust and review workflow.
We evaluate rubric design for structured reviews, moderation queues and reviewer calibration in technical communities.
Structured review calibration reference for communities and moderation teams.
We propose ledger-based moderation records that improve accountability, appeals and policy learning in research products.
Moderation auditability reference for high-trust product operations.
Works on review quality, moderation design and institutional trust systems for online science.
Strong author node for trust, moderation and review quality work.