Ranking by engagement and non‐engagement signals: Learnings from industry

Many online media platforms primarily rank items by predicted user engagement, yet we see substantial potential in incorporating non-engagement signals-such as user surveys or quality metrics-to benefit both platforms and society. Drawing on a daylong workshop with experts from various industry platforms and academia, we developed a series of propositions related to non-engagement signals that gained broad consensus. These propositions examine the relationships between engagement, non-engagement signals, and key metrics like user retention. We document each proposition with publicly available evidence, including quantitative results where possible. Given the cost and time associated with industry experimentation on non-engagement signals, we believe sharing these insights will be valuable for advancing common knowledge.

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Publication Details

Journal
Annals of the New York Academy of Sciences
Published
2025-08-20
DOI
https://doi.org/10.1111/nyas.15399
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
4.20

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article

Ranking by engagement and non‐engagement signals: Learnings from industry

Mohit Kothari, Ravi Iyer, Sanjay Kairam, Smitha Milli et al.
1 citations
Annals of the New York Academy of Sciences
Digital Marketing and Social Media
4.20
article

Ranking by engagement and non‐engagement signals: Learnings from industry

Mohit Kothari, Ravi Iyer, Sanjay Kairam, Smitha Milli, Jonathan Stray, Bonnie L. Barrilleaux, Leif Sigerson, Sana Pandey, Behnam Rezaei, J. Allen, Tom Cunningham
article en
1 citations

Abstract

Many online media platforms primarily rank items by predicted user engagement, yet we see substantial potential in incorporating non-engagement signals-such as user surveys or quality metrics-to benefit both platforms and society. Drawing on a daylong workshop with experts from various industry platforms and academia, we developed a series of propositions related to non-engagement signals that gained broad consensus. These propositions examine the relationships between engagement, non-engagement signals, and key metrics like user retention. We document each proposition with publicly available evidence, including quantitative results where possible. Given the cost and time associated with industry experimentation on non-engagement signals, we believe sharing these insights will be valuable for advancing common knowledge.

Annals of the New York Academy of SciencesVol. 1551(1)
University of Southern California (US), LinkedIn (United States) (US), Cornell University (US), Integrity Systems (United States) (US), Pollinator Partnership (US), OpenAI (United States) (US), University of California, Berkeley (US)
University of Southern California, University of California Berkeley
Openalex Percentile: Top 6%
Digital Marketing and Social Media
4.20
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Ranking by engagement and non‐engagement signals: Learnings from industry — Mohit Kothari, Ravi Iyer, et al. · Annals of the New York Academy of Sciences (2025) | TGRS Research Map | TGRS