Choose one numerator
Specify reactions, views, or forwards and do not switch metrics midway through the comparison.
Feature · Audience normalization
Normalize a captured Telegram post metric by the latest available audience snapshot at measurement time and expose fixed-horizon coverage and missing data.
Research fit
Researchers comparing sources of different sizes who need time-aligned audience normalization and explicit denominator coverage rather than raw counts or current subscriber totals applied retroactively.
Specify reactions, views, or forwards and do not switch metrics midway through the comparison.
Select a fixed observation checkpoint reached by every candidate publication before calculating rates.
Use the latest captured source audience count at or before each metric observation, not today's audience applied to old posts.
Keep missing, zero, late, or unavailable audience snapshots visible as coverage gaps rather than inventing a rate.
Use the result to compare measured metric per subscriber while acknowledging that subscribers are not identical to active viewers.
Practical module
The record ties each numerator to a historical audience denominator and a common post-age checkpoint.
Analysis contract
At one shared fixed horizon, Chat divides the selected post metric by the latest positive audience snapshot captured for that source at or before the metric observed_at time.
Eligible logical posts in selected Telegram sources or exact inherited result references. One metric is evaluated consistently across the comparison.
A time-aligned normalization recipe for comparing captured post metrics across differently sized Telegram sources.
For [candidate posts], rank [reactions, views, or forwards] relative to source audience at one shared post-age horizon. Show numerator, historical audience denominator, rate, horizon, metric time, coverage, missing reasons, and citations. Do not substitute today's audience for missing historical data.
selected post metric / latest positive source audience snapshot observed at or before the fixed-horizon metric snapshot.
# Engagement-per-subscriber recipe A time-aligned normalization recipe for comparing captured post metrics across differently sized Telegram sources. ## Calculation - Mode: normalized_engagement_ranking - Formula: selected post metric / latest positive source audience snapshot observed at or before the fixed-horizon metric snapshot. ## Query For [candidate posts], rank [reactions, views, or forwards] relative to source audience at one shared post-age horizon. Show numerator, historical audience denominator, rate, horizon, metric time, coverage, missing reasons, and citations. Do not substitute today's audience for missing historical data. ## Inputs - **Candidate posts:** A fixed selected-source/date set or references inherited from a prior result. - **Metric:** Exactly one of reactions_total, views, or forwards. - **Post horizon:** One scheduled age reached by every candidate publication. - **Audience timing:** Latest valid source snapshot no later than the metric observation. ## Expected output - Metric and audience values - Normalized rate and rank - Shared horizon and timestamps - Coverage and missing-denominator reasons - Post-level evidence links ## Coverage checks - [ ] Never use a future audience snapshot - [ ] Never replace missing audience with zero - [ ] Keep one metric across all candidates - [ ] Withhold a global winner for partial coverage - [ ] Do not equate subscribers with actual viewers
Boundaries
Founding research pilot
Bring one recurring research job and a small set of public sources. We will assess fit personally before offering a pilot.
30 founding researcher places · rolling admission · personal reply within 2 business days
Analytics cluster
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