Telegram RegisterThe public register of Telegram

Channel

E-Corner

@ecorneritalia

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

103subscribers

-1 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001034372606
TypeChannel
Username@ecorneritalia
CreatedBetween 1 January 2016 and 31 October 2016— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live15 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 15 August 2026
On Telegramt.me/ecorneritalia

Growth

103104103.56 August 2026 — 104 subscribers9 August 2026 — 104 subscribers15 August 2026 — 103 subscribers6 August 202615 August 2026
3 measurements spanning 9 days, net -1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 103–104 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Aug 2026, 03:03103-1
9 Aug 2026, 09:17104no change
6 Aug 2026, 10:45104first reading

Engagement

20 posts held, back to 16 November 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
36.9%
avg views ÷ 103 subscribers
Avg views / post
38.0
1 post measured
Reaction rate
2.63%
reactions ÷ views · ER floor
Posts in window
1
of 20 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 23 July 2026
Posts held20 (16 November 202523 July 2026)
Views total38
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 09:17 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.

Reaction mix

9 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 33.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
333.3%
👍333.3%
222.2%
🔥111.1%

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 7 of the 20 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 9reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 16 November 2025 to 23 July 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

23 Jul 2026, 15:21 UTC38 views1 reactionsread 9 August 2026
Photo

UN MUTUO, UN HASH, TRE PIATTAFORME PUBBLICITARIE Una banca spagnola chiede a un cliente di scegliere se accettare i cookie durante una richiesta di mutuo. Il cliente accetta. In quel preciso istante, email e numero di telefono, in forma crittografata ma pur sempre rintracciabile, partono verso TikTok, nonostante questo soggetto non sia menzionato da nessuna parte nella cookie policy della banca. Una ricerca di Jscra

1

8 Jul 2026, 11:55 UTC≈6,190 viewsread 9 August 2026

CHI USA L'INTELLIGENZA ARTIFICIALE IN AZIENDA NE RISPONDE PERSONALMENTE L'AI Act distingue due ruoli lungo la filiera dell'intelligenza artificiale: il fornitore, che sviluppa e immette sul mercato il sistema, e il deployer, l'azienda che lo utilizza nei propri processi operativi. Su quest'ultimo ricade la responsabilità di conformità normativa, con piena autonomia rispetto alle garanzie contrattuali offerte dal forn

29 Jun 2026, 13:11 UTC≈2,580 views1 reactionsread 9 August 2026
Photo

INTELLIGENZA ARTIFICIALE E DATI SENSIBILI: LA SICUREZZA NON SI CONTRATTUALIZZA, SI PROGETTA Il 77% dei dipendenti copia e incolla dati aziendali nei chatbot AI. Contratti riservati, perizie, offerte in negoziazione: fuori dal perimetro, ogni giorno. Il contratto enterprise regola le intenzioni dichiarate del fornitore. Non può regolare ciò che accade nel momento in cui un modello elabora semanticamente un testo: lo

🔥1

3 May 2026, 14:33 UTC80 views2 reactionsread 9 August 2026

AUTOMAZIONE E PMI: QUANTO COSTA PARTIRE DAL PUNTO SBAGLIATO Gartner stima che entro il 2027 oltre il 40% dei progetti IA agente verrà cancellato. La causa dominante è organizzativa: processi impliciti, dati sparsi, obiettivi definiti male prima ancora di scegliere uno strumento. L'automazione amplifica le caratteristiche del sistema su cui si innesta. Un flusso solido migliora. Un flusso disfunzionale produce caos p

2

6 Feb 2026, 12:39 UTC113 viewsread 9 August 2026

Privacy smartphone: come proteggere i dati aziendali senza diventare esperti di sicurezza Ogni volta che rispondi a un cliente da smartphone, scatti una foto in cantiere o apri un preventivo mentre sei in auto, il tuo telefono registra, traccia e trasmette molti più dati di quanto immagini. Non serve essere un'azienda tecnologica per subire perdite informative significative: basta un dispositivo configurato male. Se

30 Jan 2026, 17:22 UTC91 views1 reactionsread 9 August 2026

Tre segnali che il software sta cambiando (e le aziende italiane non se ne sono accorte) Il software per le PMI sta attraversando una trasformazione che molte piccole imprese italiane non hanno ancora percepito. Mentre si discute ancora se investire in digitalizzazione, il panorama competitivo si è già spostato: servizi SaaS da 120 dollari annui vengono sostituiti in 20 minuti con codice generato da intelligenza art

👍1

13 Jan 2026, 16:14 UTC90 viewsread 9 August 2026

I costi nascosti della digitalizzazione: perché le aziende pagano sempre più di quanto preventivato Quando un imprenditore decide di digitalizzare la propria PMI, il preventivo parla chiaro: 30.000 euro per il nuovo gestionale, 15.000 per l'e-commerce, 8.000 per il CRM. Budget totale: 53.000 euro. Dodici mesi dopo, il conto reale sfiora i 120.000 euro. Non per incompetenza del fornitore o per imprevisti tecnici, ma

8 Jan 2026, 10:28 UTC78 viewsread 9 August 2026

Gestione documentale personalizzata: il costo nascosto della dispersione informativa Quando un imprenditore cerca un'informazione critica – un vecchio preventivo, il dettaglio tecnico di una commessa, la comunicazione con un cliente – la dispersione è sempre la stessa: email, Google Drive, gestionale, WhatsApp, archivi cartacei. Tempo perso: 20-30 minuti per ricerca. Moltiplicato per team, giorni, anno. Il problema

6 Jan 2026, 12:09 UTC≈2,550 viewsread 9 August 2026

Zero-party data: la raccolta consensuale come alternativa concreta ai cookie di terze parti Il tramonto definitivo dei cookie di terze parti, ripetutamente annunciato e rinviato da Google Chrome, rappresenta meno una minaccia tecnologica e più un'opportunità di ripensare radicalmente il rapporto tra aziende e utenti nella raccolta dati. Mentre i grandi player internazionali hanno già investito milioni in soluzioni e

31 Dec 2025, 14:54 UTC≈2,970 viewsread 9 August 2026

Perché nove progetti di intelligenza artificiale su dieci falliscono (e come l'affiancamento professionale fa la differenza) Il 95% delle implementazioni AI non genera valore misurabile. I dati MIT 2025 rivelano che il problema non è la tecnologia ma l'approccio: ecco dove sbagliano le PMI italiane e perché l'affiancamento strategico diventa decisivo. Il 2025 si chiude con un paradosso che racconta molto dello stato

29 Dec 2025, 19:18 UTC75 viewsread 9 August 2026

Vulnerabilità pacchetti open source: perché le dipendenze software sono un problema per il business Il 23 dicembre 2025, il package npm "lotusbail" è stato rimosso dai repository dopo aver compromesso 56.000 installazioni. Il pacchetto si spacciava per una libreria legittima di gestione WhatsApp Web, conteneva codice funzionante, ma nascondeva quattro livelli di offuscamento e 27 trap anti-debugging per eludere le a

24 Dec 2025, 20:01 UTC56 viewsread 9 August 2026
Photo

🎄 Buon Natale da EBM Solution In questi giorni di festa ci fermiamo per dire grazie a chi ci ha scelto come partner nel 2025. Quest'anno ci ha insegnato che la tecnologia funziona davvero solo quando risponde a problemi concreti, non quando insegue mode. E che le relazioni solide – costruite su fiducia e risultati misurabili – valgono più di qualsiasi automazione. A tutti voi: buon Natale, tempo di qualità con chi

Showing the 12 most recent of 20 posts we hold for @ecorneritalia. 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.

Citation-graph rank

Citation-graph rank — 482,272 of 1,480,688entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

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 15 August 2026 — this entry's latest reading, not the date you are reading this.

“E-Corner” (@ecorneritalia), 103 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/ecorneritalia.

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.