Proposal: Capture latent author interest from dwell signals #16051
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Problem ------- Engagement-based ranking under-serves "silent" users who read content but do not explicitly like, reply, or retweet. The system already logs and labels multiple high-intent dwell signals (tweet detail, profile, link, fullscreen video), and aggregates them in real time, but does not expose a persistent user preference representation derived from those signals. As a result, latent interest (interest without explicit engagement) is not captured as a first-class signal. Proposed solution ----------------- Introduce online, decayed latent-interest aggregates derived from existing dwell labels, keyed by (userId, sourceAuthorId), to represent implicit long-term interest in authors. This change: - Defines AuthorLatentInterestEngagements using high-intent dwell signals (profile dwell, tweet detail dwell, long link dwell) - Adds authorLatentInterestRealTimeAggregates with exponential decay - Registers the aggregate group in ProdAggregateGroups - Ensures outputs are not filtered via aggregates_to_drop.txt - Mirrors existing user+author aggregate flag defaults (e.g. includeAnyFeature) The change is additive and does not alter existing ranking or scoring behavior. It provides a foundation for future use in scoring, mixing, or exploration to better serve silent readers. Future work (not included): --------------------------- - Consume this aggregate in scoring or mixing - Tune decay/weights via params - Extend to topic/entity latent interest
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Improvement proposal: Latent Interest Aggregates from Dwell Signals
Problem
Engagement-based ranking under-serves "silent" users who read content but do not explicitly like, reply, or retweet. The system already logs and labels multiple high-intent dwell signals (tweet detail, profile, link, fullscreen video), and aggregates them in real time, but does not expose a persistent user preference representation derived from those signals.
As a result, latent interest (interest without explicit engagement) is not captured as a first-class signal.
Proposed solution
Introduce online, decayed latent-interest aggregates derived from existing dwell labels, keyed by (userId, sourceAuthorId), to represent implicit long-term interest in authors.
This change:
The change is additive and does not alter existing ranking or scoring behavior. It provides a foundation for future use in scoring, mixing, or exploration to better serve silent readers.
Future work (not included):