Define the corpus
Choose the channels and period whose link-sharing behavior answers the research question.
Workflow · Link analysis
Analyze which domains Telegram channels share
Count external domains shared by selected Telegram channels in a defined period and inspect the posts behind each domain result.
Direct answer. The Ocean can calculate which external domains appear most often in selected Telegram sources during a defined period and link the counts back to supporting posts. Domain frequency describes sharing behavior; it does not prove endorsement, ownership, or traffic.
Research fit
Who this workflow is for
Researchers mapping the external information sources promoted or referenced by selected public Telegram channels.
Count domains
Request external-domain frequency and keep posts available behind each aggregate row.
Classify context
Inspect whether links are endorsements, criticism, citations, reposts, or incidental mentions.
Practical module
Domain-sharing analysis fields
A domain count becomes useful only after reviewing why it was shared.
Normalized domainThe hostname grouping rule, including treatment of subdomains and link shorteners.
Post countHow many in-scope posts contained the domain and the eligible corpus size.
Sharing contextObserved examples of promotion, attribution, criticism, or neutral reference.
Telegram domain-analysis request
Produce a reproducible domain table and a review sample for interpreting the counts.
For [selected sources] from [start] to [end], list the external domains shared most often. Show post counts, cite supporting posts, note link shorteners or unresolved destinations, and sample context without treating sharing as endorsement.
Inputs to set
- Corpus
- The selected Telegram sources and date range included in the count.
- Domain rule
- Whether subdomains are combined and how short links are handled.
- Sample size
- How many supporting posts to inspect for each leading domain.
Expected output
- Ranked domains with in-scope post counts
- Cited supporting-post sample
- Context classification and unresolved redirects
Review before use
- Do not infer endorsement from frequency
- Verify redirected destinations when safe
- State extraction and indexing gaps
Read the complete resource
# Telegram domain-analysis request Produce a reproducible domain table and a review sample for interpreting the counts. ## Query For [selected sources] from [start] to [end], list the external domains shared most often. Show post counts, cite supporting posts, note link shorteners or unresolved destinations, and sample context without treating sharing as endorsement. ## Inputs - **Corpus:** The selected Telegram sources and date range included in the count. - **Domain rule:** Whether subdomains are combined and how short links are handled. - **Sample size:** How many supporting posts to inspect for each leading domain. ## Expected output - Ranked domains with in-scope post counts - Cited supporting-post sample - Context classification and unresolved redirects ## Review checks - [ ] Do not infer endorsement from frequency - [ ] Verify redirected destinations when safe - [ ] State extraction and indexing gaps
Boundaries
What this does not establish
- A shared link does not necessarily imply endorsement
- Shorteners and redirects can obscure the final destination
- Counts are limited to indexed posts and extracted links in the selected period
Founding research pilot
Apply with a Telegram link-analysis task
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
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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-domains · product-citations · product-selected-sources