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Telegram profile photo for Николай Жаринов 💀

Channel

Николай Жаринов 💀

@litsomel

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Advertising · Posts · Citations · Telegram's recommendations · Cite this entry

30,719subscribers

+650 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002054687676
TypeChannel
Username@litsomel
CreatedBetween 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live24 October 2026
Measurements held49
Confirmed unchanged1 time, most recently 24 October 2026
On Telegramt.me/litsomel

Topic

Personal blog — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 87% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

30,06930,73430,401.56 August 2026 — 30,069 subscribers6 August 2026 — 30,069 subscribers6 August 2026 — 30,092 subscribers7 August 2026 — 30,110 subscribers8 August 2026 — 30,134 subscribers9 August 2026 — 30,156 subscribers10 August 2026 — 30,167 subscribers11 August 2026 — 30,178 subscribers12 August 2026 — 30,188 subscribers13 August 2026 — 30,201 subscribers14 August 2026 — 30,216 subscribers16 August 2026 — 30,251 subscribers17 August 2026 — 30,263 subscribers18 August 2026 — 30,275 subscribers19 August 2026 — 30,289 subscribers20 August 2026 — 30,296 subscribers21 August 2026 — 30,313 subscribers22 August 2026 — 30,323 subscribers24 August 2026 — 30,330 subscribers25 August 2026 — 30,320 subscribers26 August 2026 — 30,322 subscribers27 August 2026 — 30,337 subscribers28 August 2026 — 30,365 subscribers29 August 2026 — 30,381 subscribers30 August 2026 — 30,382 subscribers31 August 2026 — 30,383 subscribers1 September 2026 — 30,380 subscribers2 September 2026 — 30,383 subscribers4 September 2026 — 30,411 subscribers6 September 2026 — 30,442 subscribers10 September 2026 — 30,481 subscribers12 September 2026 — 30,504 subscribers14 September 2026 — 30,510 subscribers15 September 2026 — 30,518 subscribers17 September 2026 — 30,536 subscribers26 September 2026 — 30,509 subscribers4 October 2026 — 30,556 subscribers9 October 2026 — 30,555 subscribers13 October 2026 — 30,635 subscribers14 October 2026 — 30,672 subscribers15 October 2026 — 30,659 subscribers16 October 2026 — 30,663 subscribers17 October 2026 — 30,668 subscribers18 October 2026 — 30,677 subscribers19 October 2026 — 30,671 subscribers21 October 2026 — 30,680 subscribers22 October 2026 — 30,701 subscribers23 October 2026 — 30,734 subscribers24 October 2026 — 30,719 subscribers30,7196 August 202624 October 2026
49 measurements spanning 79 days, net +650. 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 29,969–30,834 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 49
Measured (UTC)SubscribersChange
24 Oct 2026, 08:3530,719-15
23 Oct 2026, 08:4430,734+33
22 Oct 2026, 06:3630,701+21
21 Oct 2026, 00:0630,680+9
19 Oct 2026, 19:2030,671-6
18 Oct 2026, 20:0130,677+9
17 Oct 2026, 19:2830,668+5
16 Oct 2026, 19:0030,663+4
15 Oct 2026, 22:2130,659-13
14 Oct 2026, 20:0030,672+37
13 Oct 2026, 08:2730,635+80
9 Oct 2026, 07:1830,555-1
4 Oct 2026, 18:0130,556+47
26 Sept 2026, 23:5730,509-27
17 Sept 2026, 16:5530,536+18
15 Sept 2026, 17:4130,518+8
14 Sept 2026, 02:2130,510+6
12 Sept 2026, 11:1830,504+23
10 Sept 2026, 05:3530,481+39
6 Sept 2026, 20:1830,442first reading

Engagement

119 posts held, back to 2 August 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 142 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
16.5%
avg views ÷ 30,719 subscribers
Avg views / post
5,070
44 posts measured
Reaction rate
2.98%
reactions ÷ views · ER floor
Posts in window
45
of 119 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 October 2026
Posts held119 (2 August 2026 – 23 October 2026)
Views total223,060
Reactions total6,646
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken24 Oct 2026, 04:19 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
2m 36s
Average length
2m 36s

Measured directly from 1 video 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

20,231 reactions across 115 posts, in 24 distinct kinds. The most used accounts for 54.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤11,01354.4%
🔥3,45517.1%
👍1,9359.56%
❤‍🔥1,1775.82%
😁8904.40%
💯4021.99%
custom 50219007328701650683501.73%
⚡1620.801%
🤣1290.638%
🤪1180.583%
😍1160.573%
💔1040.514%
😢820.405%
🌚560.277%
👌480.237%
🤔480.237%
😱410.203%
🤨410.203%
😭140.069%
🤯140.069%
4 further kinds360.178%

Custom emoji. One row above is a 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 count beside it is Telegram’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 117 of the 119 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 20,460 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 119 most recent posts we hold, published 2 August 2026 to 23 October 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.

Telegram Stars

Stars received
72
across the posts below
Posts paid on
22
of 117 we hold a reading for · 19%
Most on one post
26
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @litsomel. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 119 most recent posts we hold for this entry, published 2 August 2026 to 23 October 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Advertising

Ad load
1.68%
2 of 119 posts carry an ad marker
Regulatory tokens
2
posts carrying an erid · 2 distinct tokens
Median views · ads
4,310
over 2 measured posts
Median views · rest
5,270
over 115 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2SDnjdGUB5M17 October 20267 October 2026
2W5zFGvy2Zo127 August 202627 August 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 119 most recent posts we hold, published 2 August 2026 to 23 October 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

23 Oct 2026, 17:27 UTC≈1,740 views65 reactionsread 24 October 2026
Forwarded from @Evgeny_ZharinovPhoto

Друзья, сегодня на YouTube в рубрике «Человек Читающий» я буду говорить о поэзии трубадуров. Что это за культ «Прекрасной Дамы»? Как с этим могла быть связана альбигойская ересь? Почему появились биографии знаменитых трубадуров? Как возникло противоречие между этими биографиями и анонимностью средневекового искусства в целом? Что за жанры использовали в своем творчестве трубадуры? Какие поэтические приемы были наи…

❤45👍10❤‍🔥5🔥4💯1

23 Oct 2026, 17:27 UTC≈1,870 views27 reactionsread 24 October 2026

Сегодня на нашем семейном канале вышел новый ролик, где отец рассказывает про поэзию трубадуров. Не пропустите!

❤21❤‍🔥4💯1🔥1

22 Oct 2026, 15:01 UTC≈3,280 views96 reactionsread 24 October 2026
Photo

Всех приветствую! Сегодня в новом видео на канале я предлагаю вам порассуждать на важную тему: делает ли чтение нас лучше или это приятная иллюзия, которую мы создаем для себя? Посмотрим, что говорят психологи и что думали об этом великие классики. Всем приятного просмотра! Ютуб - https://youtu.be/IjUDVB4_bms ВК Видео - https://vkvideo.ru/video-227012884_456239133

❤52🔥23👍17🌚3💯1

20 Oct 2026, 17:54 UTC≈4,110 views106 reactionsread 24 October 2026
Video

О современной китайской литературе и ее внедрении в российскую школьную программу, рассказал филолог Николай Жаринов "Это же не делается нормативно. Это очень долгий процесс, потому что ты должен менять программу преподавания. Если ты меняешь программу, то тебе нужно развивать именно специалистов по восточным литературам и всему остальному", — считает культуролог. ✅ Полный выпуск смотрите в ВК и RUTUBE 📌Подписатьс…

🔥57❤21👍14custom 50219007328701650685⚡3🌚2💯2🤯1

20 Oct 2026, 17:54 UTC≈4,070 views9 reactionsread 24 October 2026

Сегодня тут последние новости комментировал на радио.

👍9

20 Oct 2026, 13:48 UTC≈3,920 views57 reactionsread 24 October 2026
Forwarded from @Evgeny_ZharinovPhoto

Друзья! В это воскресенье (25 октяьря) в культурном центре «Community» я прочитаю лекцию «Герой-любовник в мировой литературе. Кто это?» Почему тема героя-любовника во все времена волновала воображение человечества? Начиная с древнейших мифов доисторические люди в своих представлениях о силах Природы всегда создавали образ Героя, который, прежде всего, был наделен особой сексуальной силой. Кухулин у древних народо…

❤36🔥16⚡2💯2👍1

20 Oct 2026, 13:48 UTC≈3,670 views51 reactionsread 24 October 2026

У отца тут лекция грядет. Не пропустите!

⚡25❤15🔥7👍3🗿1

20 Oct 2026, 09:36 UTC≈4,130 views123 reactionsread 24 October 2026
Photo

Всем привет! На прошлой неделе проведение стрима сорвалось из-за блокировки VPN. Все починил, поэтому сегодня в 20:00 по Мск выйду в прямой эфир! Поговорим с вами о том, почему хорошие люди становятся жестокими? Разберем случаи из жизни и примеры из мировой литературы. Не пропустите! https://www.youtube.com/watch?v=Zt_ON9WbJc8

🔥69❤32custom 502190073287016506812👍8💯2

19 Oct 2026, 11:11 UTC≈4,750 views195 reactions1 Starread 24 October 2026
Photo

Проблески великой красоты… Уже говорил, что любимые мои месяцы в году — это апрель и октябрь. Да, погода в это время часто бывает не ахти какая, дожди, слякоть, но зато как остро и хорошо ощущаются внезапные, сложно предсказуемые погожие дни! Я люблю контрасты, а не стабильность. Контрасты — это искусство, стабильность — рутина. Поэтому именно в апреле и октябре мне пишется лучше всего. Еще в начале месяца мне пре…

❤136🔥31❤‍🔥11custom 50219007328701650689👍5💯2⚡1

18 Oct 2026, 17:53 UTC≈5,780 views250 reactionsread 24 October 2026
Photo

Еще пышней и бесшабашней Шумите, осыпайтесь, листья, И чашу горечи вчерашней Сегодняшней тоской превысьте. Привязанность, влеченье, прелесть! Рассеемся в октябрьском шуме! Заройся вся в осенний шелест! Замри или ополоумей! Обожаю октябрь, сегодня гулял с камерой, снимал красоту!

❤168🔥48👍11custom 502190073287016506811❤‍🔥6💯4🤔2

18 Oct 2026, 14:13 UTC≈4,670 views141 reactions1 Starread 24 October 2026
Forwarded from @punkmonkprodPhoto

Сегодня на нашем канале премьера фильма, который мы посвятили творчеству одного из лучших режиссеров современной России, Алексею Октябриновичу Балабанову. Внимание мы сконцентрировали не на биографии режиссера и не на подробном разборе его фильмов. Этого и так полно в интернете. Мы решили рассказать вам о том, как в творчестве режиссера воплотились три темы, интересовавшие мастера больше всего. Главной из них стала…

🔥80❤30💯19👍6❤‍🔥3🤬2custom 50219007328701650681

16 Oct 2026, 15:01 UTC≈5,420 views146 reactions1 Starread 23 October 2026
Photo

Сегодня на нашем семейном канале вышел новый подкаст. На этот раз говорим о магии. Получилось занимательно) Всем приятного просмотра! Ютуб - https://youtu.be/H9OVCmXIRqo ВК - https://vkvideo.ru/video-139763422_456239220

❤86👍31🔥15⚡5❤‍🔥3custom 50219007328701650683💯2🗿1

Showing the 12 most recent of 119 posts we hold for @litsomel. 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.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Forward network

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 8 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.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

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Тамара Эйдельман
@eidelman · 79,106
#53
Бальзак на душу
@balzak_on · 2,535
#54
Филологический абьюз
@bigmouth_books · 5,157
#55
ну да, литра
@nudalitra · 688
#56
Полка
@polka_academy · 21,959
#57
2 talk girls
@twotalkgirls · 17,654
#58
Manfybooks
@manfybooks · 4,367
#59
Порез бумагой
@individuumbooks · 13,776
#60
Мир фантастики
@mirf_ru · 31,443
#61
мои ночи не кончились утром
@iamfeelblue · 4,073
#62
АНФ. Думай по-своему
@alpinanonfiction · 10,908
#63
Страдающее Средневековье
@pophistory · 140,285
#64
Читай-город
@chitai_gorod_official · 141,678
#65
по краям
@admarginem · 34,085
#66
МИФ.Проза
@mifproza · 52,440
#67
Drinkcoffee.Readbooks | Книги и некниги
@drinkread · 3,971
#68
Мастриды
@mustreads · 45,047
#69
Синхронизация
@Synchronews · 57,702
#70
Искусство кино
@kinoartru · 24,108
#71
Долецкая-Doletskaya
@alionadol · 75,685
#72
Подписные издания
@izdaniya · 53,035
#73
Интеллигентка Гадова
@intelligentka_gadova · 3,161
#74
флёр паулин
@fleurrpauline · 9,662
#75
Сломанные пляски
@brokendance · 80,087
#76
Евгений Понасенков
@evgenii_ponasenkov · 78,005
#77
Зинаида Пронченко
@ZinaidaPronchenko · 74,250
#78
Arzamas
@ArzamasLive · 59,722
#79
Артифекс | История и искусство
@artifex · 19,767
#80
Павел Усачёв
@pavelusachoff · 2,927
#81
Сергей Минаев
@minaevlife · 318,079
#82
Кинопоиск | Фильмы и сериалы
@kinopoisk · 798,610
#83
страницы и судьбы
@pagesanddestinies · 1,242
#84
КАРО/АРТ
@karoartcinema · 15,998
#85
Правила жизни
@pravilamagru · 63,618
#86
Фаустов Лес
@faust21century · 73,252
#87
Юля и её Волкодав
@volkodav42 · 11,246
#88
Кроненберг нефильтрованный
@Cronenberg1664 · 38,462
#89
Cinemaholics
@cinemaholicsofficial · 30,992
#90
Ремизорро
@remizorro · 30,151
#91
Тихое Место
@thequietplace · 51,339
#92
Art Cinema | Nonconformism | Мода
@Kino_iskusstvo_vintazh · 89,316
#93

Read from Telegram’s recommendation API, most recently 7 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

PunkMonk
@punkmonkprod · 20,901
Telegram ranks this channel #1 of 96 here — alongside 95 others — read 25 September 2026
Евгений Жаринов - Лекции и анонсы
@Evgeny_Zharinov · 29,701
Telegram ranks this channel #1 of 86 here — alongside 85 others — read 8 September 2026
Артифекс | История и искусство
@artifex · 19,767
Telegram ranks this channel #20 of 89 here — alongside 88 others — read 30 September 2026
Армен и Фёдор
@armenifedor · 41,804
Telegram ranks this channel #66 of 96 here — alongside 95 others — read 29 August 2026
Филолог всея Руси
@filologofrus · 42,962
Telegram ranks this channel #67 of 95 here — alongside 94 others — read 30 September 2026

This channel appears in 5 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 24 October 2026 — this entry's latest reading, not the date you are reading this.

“Николай Жаринов 💀” (@litsomel), 30,719 subscribers as measured 24 October 2026. Telegram Register, tgregister.com/channel/litsomel.

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.