Workflow · Domain comparison

Compare domains shared by selected Telegram channels

Compare external domains appearing in selected Telegram channels with logical-post counts, first and last dates, source breakdowns, and evidence links.

Direct answer. The Ocean can count how many distinct logical posts link to each external domain inside selected channels and dates, report first and last observed appearances, list leading contributing sources, and attach a representative post. This describes sharing behavior in the indexed corpus; it does not prove website ownership, endorsement, traffic, advertising spend, or coordination.

Research fit

Who this workflow is for

Researchers examining information sources, recurring websites, or promotion patterns who need deterministic domain counts and post-level evidence rather than URL anecdotes or inferred commercial relationships.

01

Choose channels and dates

Set one source collection and publication interval so domain counts answer a reproducible comparison question.

02

Normalize links

Use extracted web links with normalized domains and distinct logical-post counting so repeated URLs inside an album do not inflate mentions.

03

Rank domain appearances

Order domains by the number of posts containing them and keep first-seen and last-seen timestamps.

04

Inspect source contribution

Review which selected channels contributed the most distinct posts for each domain.

05

Open representative evidence

Read cited posts and surrounding language before describing promotion, endorsement, partnership, or campaign behavior.

Practical module

Cross-channel domain comparison

The comparison separates deterministic link frequency from the human judgment required to interpret why a website was shared.

Normalized domainHostname extracted from eligible message URL entities, with common www prefix removed.
Post mentionsNumber of distinct logical Telegram posts containing the domain, not clicks or unique links.
First and last seenEarliest and latest stored publication timestamps inside the selected scope and period.
Source breakdownLeading selected channels and their distinct-post counts for the domain.
Example evidenceA representative recent post and permalink used to inspect language and context.
Interpretation statusObserved sharing, possible promotion lead, or unresolved relationship—not assumed endorsement.

Analysis contract

What the calculation actually does

Postgres groups normalized MessageLink domains, counts distinct logical posts, finds earliest and latest publication timestamps, and calculates per-source contributions within the selected scope.

Scope

Selected indexed Telegram channels and optional publication dates. The calculation covers extracted MessageEntity URL and text-URL links, not every textual domain reference.

Measured fields

  • Distinct-post domain mentions
  • First seen
  • Last seen
  • Top contributing sources
  • Representative post

Coverage rules

  • Albums count once per logical post
  • Only successfully extracted web links contribute
  • Counts are mentions rather than clicks
  • A representative citation does not prove the aggregate
  • Selected corpus and period bound every timestamp

Questions to ask

  • Which domains were shared most often by these channels this month?
  • Compare the websites Channel A and Channel B linked to and show first and last appearances.
  • Which selected source contributed the most posts for each leading domain?

Cross-channel domain comparison recipe

A deterministic link-analysis recipe with frequency, timing, source contribution, evidence, and interpretation guardrails.

Copy-ready query

For [selected channels] from [start] to [end], rank external domains by distinct logical posts. Show total post mentions, first and last seen, top contributing channels with counts, and a representative cited post. Treat sharing as observed behavior, not proof of endorsement, ownership, traffic, or coordination.

Deterministic calculation

domain stats

COUNT(DISTINCT logical_post) grouped by normalized domain, plus MIN/MAX publication time and per-source distinct-post counts.

Inputs to set

Sources
Selected channels whose extracted message links are eligible.
Period
Publication dates and timezone applied to every source.
Counting unit
Distinct logical post per normalized domain.
Review question
The market, narrative, or sourcing decision the link pattern will inform.

Expected output

  • Ranked normalized domains
  • Distinct-post mention counts
  • First and last appearance dates
  • Top source contribution
  • Representative evidence links

Coverage rules

  • Do not interpret counts as clicks
  • Do not infer endorsement from a link
  • Deduplicate albums
  • State extraction and corpus boundaries
  • Open representative posts before labeling promotion
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# Cross-channel domain comparison recipe

A deterministic link-analysis recipe with frequency, timing, source contribution, evidence, and interpretation guardrails.

## Calculation

- Mode: domain_stats
- Formula: COUNT(DISTINCT logical_post) grouped by normalized domain, plus MIN/MAX publication time and per-source distinct-post counts.

## Query

For [selected channels] from [start] to [end], rank external domains by distinct logical posts. Show total post mentions, first and last seen, top contributing channels with counts, and a representative cited post. Treat sharing as observed behavior, not proof of endorsement, ownership, traffic, or coordination.

## Inputs

- **Sources:** Selected channels whose extracted message links are eligible.
- **Period:** Publication dates and timezone applied to every source.
- **Counting unit:** Distinct logical post per normalized domain.
- **Review question:** The market, narrative, or sourcing decision the link pattern will inform.

## Expected output

- Ranked normalized domains
- Distinct-post mention counts
- First and last appearance dates
- Top source contribution
- Representative evidence links

## Coverage checks

- [ ] Do not interpret counts as clicks
- [ ] Do not infer endorsement from a link
- [ ] Deduplicate albums
- [ ] State extraction and corpus boundaries
- [ ] Open representative posts before labeling promotion

Boundaries

What this does not establish

  • Link counts do not measure clicks or website traffic
  • A shared domain does not prove endorsement or ownership
  • Only extracted URL entities in indexed posts are counted
  • Canonicalization does not identify every campaign variant
  • One representative citation is not proof of every mention

Founding research pilot

Apply with a cross-channel link question

Bring one recurring research job and a small set of public sources. We will assess fit personally before offering a pilot.

Apply for a 14-day research pilot

30 founding researcher places · rolling admission · personal reply within 2 business days

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Related guides

Publication notes. This page was reviewed before publication and is scheduled for review by 2026-12-19. Facts used: product-chat-domain-breakdown · product-chat-domains · product-citations · product-limitations