Latent Interest Aggregates from Dwell Signals

[dips7189]

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