Built on a decade of Telegram infrastructure. NarraPrism is the analytical layer above an indexing system that has continuously processed public Telegram channels since 2015.
Discourse grouped into evaluative claims — "the talks are a path to peace" and "the talks are a surrender" are two separate objects — not topic clusters or keyword counts. A claim that lives across many phrasings is one object.
The same narrative tracked across language communities — one claim, many expressions.
What channels publish and how their audiences actually react are tracked separately. The gap between them is often the finding.
Communities are detected from who reposts whom, not assigned manually. Surfaces who is amplifying which narrative — empirically, not by guess.
Short public cuts from the research corpus, each showing a different region and language community. Every one of them is a surface reading produced without asking the data a hard question. The depth below each is commissioned.
All three cuts are surface readings; the depth below each is commissioned.
A public page states a direction. A commissioned cut states an answer. One subject goes in - an actor, a brand, a claim, a corridor, a location, a name. This is the shape of what comes back, with identifiers withheld here because this is a public page.
First results in days rather than months, across any of the languages in the index, answered backwards across years of history as readily as forwards. Send one subject and we will come back with a short read on what the environment holds on it.
NarraPrism is the third layer in a continuous research stack. The directory and search products generate the indexing pipeline and operational dataset that the analytical layer is built on.
Structured public directory organized by topic, country and language. 132,000+ communities published across 271 categories, 72 languages, 154 countries. The original indexing system, continuously maintained.
Dedicated search across tens of millions of public Telegram communities, with structured filters for activity, language, country, member count. The retrieval layer for researchers, journalists, OSINT practitioners and NGOs.
Analytical layer for content intelligence and large-scale narrative analysis. Built on the corpus, repost graph and channel metadata accumulated over the previous decade. Current research corpus: 84 languages, 12 months.
The full indexed corpus by language. The research corpus (see Coverage below) is drawn from this base.
Twelve months of posts, September 2025 – August 2026, from public channels and discussion groups on news, politics, security and society. Every figure below is computed from the archived corpus and can be reproduced from it.
Language not determined for about 10% of posts. Volumes reflect current collection and grow as coverage expands.
The index behind this research holds 18M+ Telegram channels and groups across 140+ languages and grows every day, with 67M+ further channels discovered and queued. Topics range from politics, security and economy to finance and crypto, technology, education, religion, health, commerce, media and local communities, across Eastern Europe, the Middle East and North Africa, Iran and Central Asia, South and Southeast Asia, Europe, Latin America and Africa.
The research corpus above is a small part of this index. Any topic, language or region can be collected and analysed in depth on request.
Every area below is a first cut of the data we already hold. Any of them — or any other topic, region or language — can be expanded substantially: targeted collection of additional channels and groups, longer history, comments and audience reactions, and custom research built around a client's questions.
The global Telegram agenda across 84 languages: shared and diverging events, how fast the same event travels between languages, and what draws audience response.
Chinese-language channels on fraud operations in Cambodia, Myanmar, the Philippines and Thailand: schemes, recruitment, exposure and audience reaction.
Prices, currencies, energy and wages as discussed by audiences in Russian, Persian, Turkish, Arabic, Ukrainian and Spanish.
Agenda, economy, labour migration and infrastructure across the language communities of the region.
Economy, water and climate, culture, education and everyday life in the second-largest language community of the corpus.
Agenda, economy and security in Venezuela, Cuba, Mexico, Colombia and Argentina.
From a pilot study (June 2026) on a 3.4M-post corpus covering Trump, Putin and Zelensky across eight language ecosystems. Each finding is grounded in a stated method and explicit limitations.
Posts about Putin, grouped by channel stance toward Trump. In pro-Trump channels, war-framed posts receive 3.5× more likes per 1K views than peace-framed posts, with anger near zero on both. In anti-Trump channels, peace-framed posts draw strong anger (6.56 per 1K views). The same word performs a different function for each audience — measured in reactions, not in what channels publish.
A 57% gap, measured on audience reactions rather than channel output. Among the most-forwarded sources in Russian-language coverage of Putin, pro-government and Ukrainian outlets appear at near-equal volumes. What channels publish and how their audiences respond can point in different directions.
US pro-Trump, Russian pro-war and Ukrainian opposition channels all carry critical framing of Zelensky — through different sources, in different languages, for different reasons. Convergence without coordination is harder to detect than a single coordinated campaign, and easy to misread as one.
Communities are detected from who-reposts-whom on a 6,761-node, 9,696-edge graph. No manual labels in the detection step. Names assigned post-hoc by reading the channels in each cluster and describe only language, region and stance. Ranking reflects this corpus (posts about three leaders), not the relative size of any movement.
Count = channels and source-nodes assigned to the community. Cross-reference: 355 narrative-to-community links computed with weight = share of narrative posts originating in the community.
The global Telegram agenda, September 2025 – August 2026: which events each language community discussed, where agendas converged and diverged, how fast the same event travelled between languages, and what drew audience response. Built on the full research corpus, with every figure reproducible from the archive.
What a channel publishes and how its audience reacts are two different opinions. NarraPrism separates them by default — and the gap is frequently where the analytically interesting result lives.
A single claim tracked across languages. Convergence between unrelated infrastructures (no shared sources, similar messaging) is detectable because the analysis sits above language.
Communities are detected from amplification structure, not assigned by hand. Surfaces who is reposting whom — and which narrative is being amplified by which empirical cluster of channels.
Each narrative is linked to the communities amplifying it, with weights. Lets the analyst answer: "this claim — which network is carrying it, and how strongly?"
NarraPrism ingests content from public Telegram channels. The current research corpus covers twelve months (September 2025 – August 2026) across 84 languages, drawn from a continuously updated index of channels and groups meeting activity and size criteria. The corpus is archived; every published figure can be reproduced from it.
Narratives are extracted as evaluative claims and deduplicated into canonical objects across languages and channel groups. Channel stance and audience reaction are treated as separate analytical layers — the gap between them is, in practice, where the interesting result tends to sit. Audience signal is derived from platform engagement, normalized to within-language baselines, not from generated emotional labels.
Communities are detected from the repost graph via graph-based community detection — no manual labels in the detection step. Each narrative carries weighted attribution to the communities amplifying it.
Every report states confidence bounds and known failure modes. Detailed methodology, validation procedures and reproducible query sets are provided to institutional partners under NDA.
How audiences in different language communities receive a policy decision — channel framing vs audience reaction, before mainstream coverage catches up.
Cross-language narrative briefs on contested topics, with traceable method and reproducible queries — citable in publications.
Detection of narrative environments that affect mission areas (migration, conflict, human rights) — empirical, not anecdotal.
Repost-graph traces from a story back to source communities. Convergence patterns between unrelated networks.
Narrative risk around markets, sectors and counterparties across languages — early signals with traceable method.
How a brand, organization or topic is framed across language communities, and which networks carry that framing.
An international team of Telegram researchers and data engineers — a decade of continuous work in this space.
The team began operating large-scale messaging communities before Telegram existed. When Telegram introduced supergroups and a proper moderation architecture in 2015, that early operational involvement produced the first structured dataset on the platform — maintained and extended ever since.
Over a decade, the collection infrastructure has processed a significant portion of the Telegram ecosystem. The majority is filtered at the collection layer — inactive accounts, short-lived groups, communities below threshold. What is retained is the operational corpus on which NarraPrism's analytical layer runs.
NarraPrism is an independent commercial company. It is not affiliated with, funded by, or acting on behalf of any government, political party, campaign or advocacy movement, and takes no position on the conflicts and actors it measures. One methodology is applied to all sides. NarraPrism does not provide influence, campaign or content-promotion services.
Verification, team credentials and references are provided to institutional partners under NDA on request.
NarraPrism is currently in private access. We work with organizations that have a defined use case — research institutions, policy and public-sector teams, NGOs, media, and corporate risk and compliance teams. Custom analysis and sample reports are available on request.
Direct contact: research@narraprism.com
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