Telegram RegisterThe public register of Telegram

Channel

Охотники за поведением

@profiling_srccs

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

2,354subscribers

+1 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-1001107974936
TypeChannel
Username@profiling_srccs
CreatedBetween 1 February 2017 and 28 February 2019— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/profiling_srccs

Growth

2,3532,3552,3546 August 2026 — 2,353 subscribers6 August 2026 — 2,353 subscribers9 August 2026 — 2,355 subscribers12 August 2026 — 2,354 subscribers6 August 202612 August 2026
4 measurements spanning 6 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 2,353–2,355 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 05:182,354-1
9 Aug 2026, 12:382,355+2
6 Aug 2026, 05:482,353no change
6 Aug 2026, 02:122,353first reading

Engagement

12 posts held, back to 3 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
20.8%
avg views ÷ 2,354 subscribers
Avg views / post
490
9 posts measured
Reaction rate
3.54%
reactions ÷ views · ER floor
Posts in window
9
of 12 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 held12 (3 July 20267 August 2026)
Views total4,413
Reactions total156
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:38 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
8m 46s
Average length
2m 12s

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

221 reactions across 12 posts, in 13 distinct kinds. The most used accounts for 36.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍8036.2%
🔥6027.1%
3616.3%
🤔114.98%
💯83.62%
😁62.71%
👏52.26%
🎉31.36%
👀31.36%
😍31.36%
🤝31.36%
🤩20.905%
💘10.452%

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 12 of the 12 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 221reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 12 most recent posts we hold, published 3 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.

Telegram Stars

Stars received
3
across the posts below
Posts paid on
3
of 12 we hold a reading for · 25%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @profiling_srccs. 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 12 most recent posts we hold for this entry, published 3 July 2026 to 7 August 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.

Recent posts

7 Aug 2026, 10:59 UTC127 views13 reactionsread 7 August 2026
Photo

Идеальность соискателя (с точки зрения биографии и послужного списка) не всегда является гарантией безопасности компании в будущем. Гораздо важнее, чтобы человек влился в коллектив, разделял идеологию компании, уважал руководство и коллег, соблюдал внутренние правила. 📌 В противном случае даже высококвалифицированный специалист может стать антилидером и саботировать внутренние процессы из-за несогласия с политикой

👍5💯4🔥21🤝1

4 Aug 2026, 11:14 UTC847 views8 reactionsread 7 August 2026
Photo

Точность и прогностическая ценность аналитической работы профайлера частично зависит от выбора наиболее подходящей методики или комбинации методик анализа поведения человека. К сожалению, поведенческим аналитикам легко сбиться с пути при выборе оптимального комплекса методов и тактических приемов. Не имея под рукой подробной инструкции и привычки использовать в работе разнообразный инструментарий, аналитики становя

3👍3🔥2

31 Jul 2026, 11:00 UTC388 views15 reactions1 Starread 7 August 2026
Photo

Первый эшелон борьбы с рисками «человеческого фактора» в управлении персоналом – это процедура принятия кандидата на работу. Именно в этот момент мы помогаем не пропустить неблагонадежного человека в компанию. Для этого о кандидате собирается довольно значительный объем информации: 📌биографические данные, 📌сведения об опыте, 📌информация из социальных сетей 📌и многое другое. Здесь в работе помогает OSINT (прим. – Op

👍6🔥54

28 Jul 2026, 07:59 UTC473 views14 reactionsread 7 August 2026
Video

В пятницу мы говорили о том, что широкий перечень вопросов — один из способов увидеть немного больше, чем собеседник хотел бы показать. Но важно не только их количество. Не менее важно, как именно они сформулированы. Об этом мы уже рассказывали в одном из предыдущих постов. А сегодня хотим поделиться шуточным роликом, который наглядно показывает: даже большой список вопросов не поможет получить нужную информацию, е

😁6👏5🔥3

24 Jul 2026, 07:59 UTC540 views19 reactionsread 7 August 2026
Photo

Как-то раз к нам пришел собственник бизнеса, который подозревал, что кто-то из сотрудников ведет себя нечестно. Запрос не новый, но следующая его просьба была неожиданной. Он, видимо насмотревшись различных роликов, где «профайлеры» якобы считывают ложь по одному взгляду, жесту или движению бровей, предложил: «Давайте я поставлю перед вами всех своих сотрудников, вы пройдетесь, посмотрите на них и найдете того, кто

🔥8👍7🎉2🤝2

22 Jul 2026, 10:59 UTC432 views21 reactionsread 7 August 2026
Photo

Почему ложь отражается в поведении человека? Мы часто повторяем: «Ложь — это стресс, но не всякий стресс — это ложь». и обычно при этом заостряем внимание на второй половине фразы, чтобы на корню пресечь интерпретацию любых признаков нервозности как обмана. Но сегодня предлагаем подробнее разобраться с первой частью этого утверждения. На наш взгляд это поможет понять, почему многим кажется, что они интуитивно чувст

👍8🔥65🤔2

21 Jul 2026, 07:59 UTC381 views20 reactions1 Starread 7 August 2026
Forwarded from @artemov_securityPhoto

📚 Хорошие плохие чувства. Почему эволюция допускает тревожность, депрессию и другие психические расстройства - Рэндольф Несси (2021) Язык: RU 🇷🇺 Описание: Психические расстройства – настоящий бич для нашего биологического вида. Но почему в человеческой жизни так много душевных страданий? Отчасти дело в том, что такие эмоциональные состояния, как тревожность, плохое настроение и скорбь, сохранялись и формировались

👍86🔥4🤩2

17 Jul 2026, 08:03 UTC568 views26 reactionsread 7 August 2026
Video

Почему иногда мы «чувствуем», что с человеком что-то не так? И можно ли доверять этим ощущениям? В интервью каналу «Жиза» Анна Кулик рассказывает, что такое интуиция с точки зрения профайлинга и какую роль она играет в анализе поведения человека. А тут можно посмотреть его целиком. #профайлинг #профайлер #мывсми 🛡 Сайт | ⭐ Дзен | 🌐 ВК | 🔴 МАХ

8👍8🔥6🤔4

14 Jul 2026, 08:03 UTC657 views20 reactionsread 7 August 2026
Video

Вы наверняка замечали, что порой вопросы или реплики собеседника звучат вроде бы безобидно, но почему-то ранят. Например: «Ты в следующий раз так же поздно приступишь к задаче, и мы снова рискнём не успеть?» Формально это вопрос. Но по сути — утверждение-упрёк, замаскированный под вопрос. И подобных ситуаций в нашей жизни гораздо больше, чем кажется. _ Любое общение происходит как бы в двух параллельных реальностя

👍11😍3🔥2🤔2💘1💯1

10 Jul 2026, 08:00 UTC703 views18 reactionsread 7 August 2026
Photo

В какой момент желание помочь превращается в ловушку? Наш ученик рассказал историю о сдаче квартиры. На её примере разбираем: 📌 как работают бытовые манипуляции; 📌 как мы незаметно для себя оказываемся в роли Спасателя; 📌 как вовремя вернуть себе контроль над ситуацией. Прочитать ➡️ https://anna-kulik.ru/istoriya-o-tom-kak-ne-popastsya-na-manipulyaciyu/ #защитаотманипуляций #профайлинг 🛡 Сайт | ⭐ Дзен | 🌐 ВК | 🔴

👍8🔥4💯3🤔3

7 Jul 2026, 08:02 UTC619 views25 reactionsread 7 August 2026
Forwarded from @artemov_securityPhoto

🪄 Пост о подгорании моей пятой точки Как же меня бомбануло...скинули мне тут статью: ➡️ Источник 💬 "Новоявленный целитель Валерий Кустов наделал много шуму на ТВ. Он берётся лечить любого и от любой болезни." Когда я вижу подобное, особенно, на главном канале нашей страны, я не верю, что в 2026 году мы возвращаемся в 90-е к формату Кашпировского. Объяснение простое - сейчас непростое время и всегда в такие време

🔥11👍65👀3

3 Jul 2026, 08:03 UTC≈2,150 views22 reactions1 Starread 7 August 2026
Video

Весь прошедший учебный год мы публиковали небольшие фрагменты из уроков нашего дистанционного курса, а сейчас решили собрать их в одном месте: 1. Эффект Манделы. Почему мы коллективно помним то, чего не было?! 2. Какой НЕ должна быть профайлинговая беседа? 3. Осторожно: эффект Форера/Барнума. Язык манипуляторов и "гороскопов". 4. Выкиньте из головы советы про закрытую позу. 5. Что влияет на "чтение" жестов? 6.

👍10🔥74🎉1

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

Citation-graph rank

Citation-graph rank — 18,268 of 1,160,990entries 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.

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 4 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.

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.

“Охотники за поведением” (@profiling_srccs), 2,354 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/profiling_srccs.

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.