https://youtube.com/shorts/2SUKPmFuABI?is=dvkTjhXwcBJX13_W

Channel
UnisVers 𝑙'𝐼𝑛𝑓𝑜
@unis_vers
On this record: Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
2,090subscribers
-3 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
Register entry
| Telegram ID | -1001085693384 |
|---|---|
| Type | Channel |
| Username | @unis_vers |
| Created | Between 1 September 2016 and 30 September 2017— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/unis_vers |
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 17:34 | 2,090 | -5 |
| 10 Aug 2026, 03:11 | 2,095 | +1 |
| 7 Aug 2026, 10:20 | 2,094 | +1 |
| 7 Aug 2026, 02:15 | 2,093 | no change |
| 7 Aug 2026, 02:04 | 2,093 | first reading |
Engagement
22 posts held, back to 31 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.03%
- avg views ÷ 2,090 subscribers
- Avg views / post
- 126
- 22 posts measured
- Reaction rate
- 1.74%
- reactions ÷ views · ER floor
- Posts in window
- 22
- of 22 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 17 of 22 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 7 August 2026 |
|---|---|
| Posts held | 22 (31 July 2026 – 7 August 2026) |
| Views total | 2,774 |
| Reactions total | 38 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 16:58 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
- Video runtime
- 7m 10s
- Average length
- 1m 48s
Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
38 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 21.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 8 | 21.1% | |
| ❤ | 6 | 15.8% | |
| 👏 | 6 | 15.8% | |
| 😢 | 6 | 15.8% | |
| 😁 | 5 | 13.2% | |
| 😱 | 4 | 10.5% | |
| 👎 | 3 | 7.89% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 17 of the 22 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 38reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 31 July 2026 to 7 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
🔗 Pour toujours plus d’infos, rejoignez-nous : https://t.me/connexio
Cliché rare Poilus dans les tranchées de 14-18, à qui on vient juste d'apprendre qu'ils se battent pour que leurs arrière petits enfants puissent avoir des cheveux bleus, des tatouages en tête de mort sur l'épaule et des piercings plein la bouche, puissent brailler comme des possédés contre le patriarcat toxique des néo-fascistes et puissent se coller les mains à la superglu sur le bitume par "anxiété climatique"... …
😢3
https://pierredecoderleco.substack.com/p/je-me-suis-trompe-partie-2-du-pere?r=1ff8sj&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
👍1
J'ai pas prévu de voter en 2027, vu que je ne crois pas un instant à "la démocratie républicaine française", mais il se peut que je me bouge pour mettre un bulletin en faveur du candidat qui s'engagera à dégager toute la décoration en style "Néo-Tuche" de Brigitte à l'Elysée... https://t.me/aubontouite_francais
👍1😁1
Rendons gloire à Macron pour avoir facilité 2 métiers, qui auparavant, étaient très compliqués : - Médecin : Doliprane/ Vaccin/ Chimiothérapie/ Euthanasie. - Enquêteur : C'est les russes. C'était donc ça, le choc de simplification ! Bravo Manu ! https://t.me/aubontouite_francais
👍2
Imagine ! Tu réalises le rêve de toute l’humanité depuis qu’elle a commencé à lever les yeux vers le ciel. Tu réalises le plus bel exploit de toute son histoire. Et tu finis par en perdre toutes les images, tous les échantillons et toute la technologie. Tu parles d’une malchance ! https://t.me/aubontouite_francais
😁2
La petite zone entre la terrasse en bois et la ligne de petites boules rouges a coûté 1,5 Mds €. Il s’agit de la piscine la plus chère de l’histoire et de l’une des opérations financières effectuées avec de l’argent public, les plus opaques… C’est ça la gestion socialiste… https://t.me/aubontouite_francais
😱2
Accusation complotiste stupide sur BFM concernant les origines russes des incendies en France ! Caroline Thominet a provoqué un véritable séisme ce mercredi matin sur BFM TV. Présidente de l’ONG Doc4Ukraine et présentée comme analyste géopolitique, elle a osé lier les incendies de forêt en France à une possible action russe. Vers 11h40, elle a affirmé qu’il fallait se poser des questions sur les ingérences russes. E…
😢1
Parce que bien évidemment, Poutine n'a que ça à foutre de s'attaquer à Glucksman qui doit plafonner à 0,7% d'intentions de vote et sa meuf Léa Salamé qui avait promis de quitter l'antenne d'un service public que plus personne n'écoute si son mec se présentait à l'élection... https://t.me/aubontouite_francais
😁1
Coucou Coucou Emmanuel Macron, La France prétend protéger les enfants en censurant les réseaux sociaux, mais condamne a de la prison ferme, des gens qui traquent les pédophiles, alors qu’on devrait les décorer. … Ça commence à se voir tu sais ?... https://t.me/aubontouite_francais
😁1
AVANT, quand tu voulais aller chez le médecin, t'appelais le médecin et tu allais le voir. MAINTENANT t'es obligé de passer par Doctolib. AVANT quand tu voulais aller chez un spécialiste, t'appelais le spécialiste et tu allais le voir. MAINTENANT tu dois d'abord passer par un généraliste (donc par Doctolib). AVANT, quand tu voulais refaire ton passeport, t'achetais un timbre fiscal au tabac, tu allais en Mairie, tu…
❤2
Showing the 12 most recent of 22 posts we hold for @unis_vers. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.
“UnisVers 𝑙'𝐼𝑛𝑓𝑜” (@unis_vers), 2,090 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/unis_vers.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.