Telegram RegisterThe public register of Telegram

Channel

Лампа Ильича

@spbsetu

On this record: Growth · Engagement · Reactions · Posts · Citations · Cross-platform identity · Cite this entry

1,994subscribers

+8 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001195710074
TypeChannel
Username@spbsetu
Created11 December 2020measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/spbsetu

Growth

1,9861,9941,9906 August 2026 — 1,986 subscribers6 August 2026 — 1,986 subscribers9 August 2026 — 1,991 subscribers12 August 2026 — 1,994 subscribers6 August 202612 August 2026
4 measurements spanning 6 days, net +8. 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 1,985–1,995 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 06:031,994+3
9 Aug 2026, 16:031,991+5
6 Aug 2026, 06:321,986no change
6 Aug 2026, 03:511,986first reading

Engagement

18 posts held, back to 23 July 2026the 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
21.6%
avg views ÷ 1,994 subscribers
Avg views / post
431
18 posts measured
Reaction rate
1.73%
reactions ÷ views · ER floor
Posts in window
18
of 18 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 7 August 2026
Posts held18 (23 July 20267 August 2026)
Views total7,752
Reactions total134
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 17:09 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

118 reactions across 17 posts, in 9 distinct kinds. The most used accounts for 21.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥2521.2%
custom 54609371088206205462319.5%
❤‍🔥1815.3%
1714.4%
👍1311.0%
😁86.78%
custom 545843134329575817965.08%
custom 545840945614241794643.39%
custom 546064527008782381543.39%

Custom emoji. 4 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.

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 18 of the 18 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 134reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 18 most recent posts we hold, published 23 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

7 Aug 2026, 08:39 UTC201 views9 reactionsread 7 August 2026
Photo

#лето_лаба ⚡️ Не опять, а снова мы в УНЛ ПРОБЛАБ CDIO-ФИБС. Поймали за работой инженера лаборатории Валерия Гущина: - Чем вы занимаетесь в лаборатории этим летом? - Лаборатория для меня инженерный храм. Поэтому отвечая на ваш вопрос, скажу «верю в совершенствование своих профессиональных навыков». - Чем лето в лабе/ЛЭТИ отличается от учебного года? - Тишиной, покоем и возможностью замедлиться, которых так не хватае

🔥4custom 54609371088206205463👍1custom 54584094561424179461

6 Aug 2026, 09:15 UTC323 views20 reactionsread 7 August 2026
Photo

🔒 Тайная комната ЛЭТИ: 3088 диссертаций за закрытой дверью Вы когда-нибудь задумывались, куда попадают докторские и кандидатские, после того как автор произнес «спасибо за внимание», а совет проголосовал «за»? В ЛЭТИ ответ на этот вопрос спрятан за дверью, которую вы никогда не откроете просто так. Внутри — стеллажи до самого потолка, а на них, в алфавитном порядке, выстроены красные, синие и зеленые корешки —3088

11🔥6custom 54609371088206205463

5 Aug 2026, 08:00 UTC351 views13 reactionsread 7 August 2026

Posted without readable text

custom 545843134329575817943🔥3custom 54584094561424179463

4 Aug 2026, 10:50 UTC361 views7 reactionsread 7 August 2026

Posted without readable text

custom 54606452700878238154custom 54584313432957581792custom 54609371088206205461

4 Aug 2026, 08:33 UTC240 views5 reactionsread 7 August 2026
Forwarded from @LETITodayPhoto

🤖 Можно ли создать «железо» для ИИ, которое будет работать быстрее и потреблять меньше энергии? Именно над этим работают ученые ЛЭТИ. Они разработали первый магнонный резервуарный компьютер на основе керамического железо-иттриевого граната (ЖИГ) — доступного материала, который значительно дешевле традиционных решений. Вместо привычной электроники вычисления здесь выполняют спиновые волны (магноны). Такая технология

👍2custom 54609371088206205462😁1

1 Aug 2026, 08:30 UTC437 views3 reactionsread 7 August 2026

#Новость_недели 👁️ Взгляд человека оказался таким же уникальным, как отпечатки пальцев Психологи доказали: то, куда мы смотрим в первую очередь, уникально для каждого из нас. С помощью VR-очков и алгоритмов ИИ ученые выяснили, что по особенностям взгляда человека можно уверенно узнать даже спустя неделю среди десятков других людей. Что это значит? Алгоритмы проанализировали не только траекторию глаз, но и смысловы

🔥3

31 Jul 2026, 08:20 UTC435 views8 reactionsread 7 August 2026
Photo

#Научи_ученого ✨ Сегодня о том, кто вдохновляет, рассказал аспирант, ассистент и младший научный сотрудник кафедры РС Никита Тымченко. Молодой ученый поделился, что больше всего его восхищает эволюция средств связи. И это неудивительно: ведь именно благодаря этому вы можете прямо сейчас читать наш канал.

❤‍🔥71

30 Jul 2026, 09:02 UTC496 views3 reactionsread 7 August 2026
Photo

🤩 Ученые ЛЭТИ – на II Международной конференции «Функциональные халькогениды: физика, технология и применение» В рамках мероприятия, проходящем в МИЭТ, сотрудники ЛМРФ им. Б. А. Калинокоса, а именно зав. кафедрой ФЭТ Андрей Александрович Никитин и магистрант ФЭЛ Даниил Хрошин выступили с докладами об исследованиях, которы ведутся в Лаборатории при поддержке Минобрнауки РФ. 🔵В докладе Андрея Александровича «Исследов

🔥3

29 Jul 2026, 08:20 UTC542 views14 reactionsread 7 August 2026
Photo

🎉 Разработка молодого ученого ЛЭТИ – в топ-5 лучших медицинских изобретений по мнению экспертов Роспатента Роспатент представил пять выдающихся новинок в области медицины от российских ученых. Среди них – шлем для помощи людям со слепотой, созданный ассистентом кафедры БТС Димитриосом Илиасовичем Палогианнидисом: В отличие от существующих аналогов, он способен оценивать уровень угрозы безопасности жизни пользователя

❤‍🔥9👍3custom 54609371088206205462

28 Jul 2026, 10:20 UTC494 views9 reactionsread 7 August 2026
Photo

📱 Эти обои редакция создавала для вас в процессе осмысления бытия... и интегралов Скачивайте, ставьте на заставку и пусть ваши эмоции совпадают с состоянием лэтишных котиков, которые тоже пытаются все это понять! ‍

custom 54609371088206205465🔥2😁2

Showing the 12 most recent of 18 posts we hold for @spbsetu. 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 — 686,986 of 1,169,250entries 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

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

Named by 2 registered channels — 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.

Cross-platform identity — Wikidata

A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.

Q4407708 on Wikidata, read 9 August 2026
LabelVladimir Ulyanov (Lenin) LETI Saint Petersburg State Electrotechnical University
DescriptionSaint Petersburg Electrotechnical University is one of the oldest Russian higher education institutions.
X / Twitter@spbgetu
Official sitehttps://etu.ru/

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.

“Лампа Ильича” (@spbsetu), 1,994 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/spbsetu.

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.