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Channel

FARIDA STORE

@faridastorre

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

7,739subscribers

-178 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001142743229
TypeChannel
Username@faridastorre
CreatedBetween 1 July 2016 and 29 February 2020 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live6 September 2026
Measurements held12
Confirmed unchanged1 time, most recently 6 September 2026
On Telegramt.me/faridastorre

Growth

7,7397,9177,8287 August 2026 — 7,917 subscribers7 August 2026 — 7,917 subscribers7 August 2026 — 7,916 subscribers10 August 2026 — 7,903 subscribers14 August 2026 — 7,892 subscribers17 August 2026 — 7,878 subscribers20 August 2026 — 7,865 subscribers24 August 2026 — 7,847 subscribers27 August 2026 — 7,823 subscribers30 August 2026 — 7,779 subscribers2 September 2026 — 7,759 subscribers6 September 2026 — 7,739 subscribers7 August 20266 September 2026
12 measurements spanning 31 days, net -178. 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 7,712–7,944 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
6 Sept 2026, 23:177,739-20
2 Sept 2026, 14:437,759-20
30 Aug 2026, 12:437,779-44
27 Aug 2026, 11:457,823-24
24 Aug 2026, 01:457,847-18
20 Aug 2026, 08:227,865-13
17 Aug 2026, 11:377,878-14
14 Aug 2026, 07:597,892-11
10 Aug 2026, 19:167,903-13
7 Aug 2026, 12:407,916-1
7 Aug 2026, 05:157,917no change
7 Aug 2026, 05:037,917first reading

Engagement

10 posts held, back to 15 December 2024the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 19 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.57%
avg views ÷ 7,739 subscribers
Avg views / post
199
2 posts measured
Reaction rate
0.893%
reactions ÷ views · ER floor
Posts in window
2
of 10 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 1 of 2 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 27 August 2026
Posts held10 (15 December 202427 August 2026)
Views total398
Reactions total2
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 20:26 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
56s
Average length
28s

Measured directly from 2 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

99 reactions across 8 posts, in 7 distinct kinds. The most used accounts for 65.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
6565.7%
👍1515.2%
🔥99.09%
❤‍🔥44.04%
💔33.03%
🗿22.02%
💘11.01%

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 8 of the 10 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 99 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 15 December 2024 to 27 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

27 Aug 2026, 21:28 UTC174 viewsread 28 August 2026
Photo

Париж и обезьяна на мотоцикле Собрано из двух фотографий: девушка на улице и обезьяны на мотоцикле. Обе — ниже. Use @Image1 as the exact reference for the woman’s face, hair, outfit and bag. She walks calmly toward the camera while the camera operator continuously walks backward, keeping her centered in frame. Use @Image2 as the exact reference for two monkeys riding one motorcycle. 0–4 seconds: the woman confid

26 Aug 2026, 16:46 UTC224 views2 reactionsread 28 August 2026
Photo

Устроили скидки на самое вкусное 🍌 🎬 Seedance 2.5 −55% Видео до 30 секунд со звуком, до 1080p. Ролик теперь от 67 кредитов — дешевле у нас ещё не было. 🖼 Nano Banana −30% Та самая нейросеть для картинок и правок фото (Pro и вторая версия). Генерация от 16 кредитов. Новичкам после регистрации даём пробные кредиты.

2

31 Jul 2026, 11:07 UTC≈1,030 views4 reactionsread 28 August 2026
Video

🔥 Seedance 2.5 наконец-то показали. Неотличимо от реальности. Новый флагман ByteDance. На видео — один и тот же момент: сверху черновая сцена из кубиков, снизу готовый кадр. Камера та же, секунда в секунду. Что умеет: ⏱️ 30 секунд одним дублем — вдвое длиннее прошлого поколения, а продлением история тянется до нескольких минут 📸 До 50 референсов за раз — 30 фото, 10 видео и 10 аудио: герои, локация и продукт собира

2👍2

25 Jul 2026, 13:29 UTC≈1,160 viewsread 28 August 2026
Video

🎬 Одна страница манги. Две нейросети. Один и тот же видеодвижок. Мы дали двум моделям — GPT‑5.6 Sol и Opus 5 — одну задачу: «оживи эту страницу». Промпт они писали сами: сами решали, что тут главное и куда вести камеру. Оба промпта ушли в Seedance 2.0 с одинаковыми настройками. GPT‑5.6 Sol заходит внутрь сцены: камера ныряет в панель, страница перестаёт быть страницей. Opus 5 оставляет лист листом и работает светом

22 Mar 2026, 11:49 UTC≈4,540 views11 reactionsread 28 August 2026
Video

🛠 УТИЛИТЫ — ИИ-ИНСТРУМЕНТЫ В ОДИН КЛИК Запустили новый раздел на Fyro AI — готовые инструменты для обработки фото. Никаких промптов, никаких настроек моделей — загрузил фото и получил результат. Эффекты: — Взрыв за спиной — кинематографичный взрыв в слоу-мо, модель сама анализирует глубину и перспективу кадра — Поток воды — волна накатывает из-за спины героя, добавляет движение и глубину сцены — Металлическая к

7🗿2👍1💘1

2 Mar 2026, 14:43 UTC≈5,040 views6 reactionsread 28 August 2026

🚀 Google представил Nano Banana 2 — новое поколение ИИ-модели для генерации и редактирования изображений (официально Gemini 3.1 Flash Image). Эта версия сочетает скорость Flash с возможностями Pro: быстрее генерирует визуал, точнее понимает сложные инструкции и лучше работает с текстом на картинках. 🧠 Что нового: - Рассуждающее ядро, понимает контекст и логику запроса. - Чёткий читаемый текст прямо в изображении — и

4🔥2

31 Dec 2024, 21:02 UTC≈11,200 views30 reactionsread 28 August 2026

😀 😀😀😀😀😀 😀😀😀😀😀 🪄 💥

21🔥6💔3

17 Dec 2024, 09:49 UTC≈11,300 views19 reactionsread 28 August 2026
Photo

👟: New Balance 610T Код товара: ML610TF • Доступные размеры: 36 EU - 45 EU 💰Цена: от 6.500₽ - Есть другие расцветки! 📍Теги для быстрого поиска: #Newbalance #Low Понравилась пара или вещь? Не стесняйся! Напиши нам и мы её привезем в кратчайшие сроки @RolyaSupport

16👍3

16 Dec 2024, 10:04 UTC≈7,700 views16 reactionsread 28 August 2026
Photo

👟: VLONE Sneakers Код товара: VLSN001WO • Доступные размеры: 36 EU - 45 EU 💰Цена: от 9.300₽ - Есть другие расцветки! 📍Теги для быстрого поиска: #VLONE #Low Понравилась пара или вещь? Не стесняйся! Напиши нам и мы её привезем в кратчайшие сроки @RolyaSupport

7❤‍🔥4👍4🔥1

15 Dec 2024, 08:41 UTC≈4,770 views11 reactionsread 28 August 2026
Photo

👟: Nike Blazer Jumbo Код товара: DQ1471-600 • Доступные размеры: 35.5 EU - 42 EU 💰Цена: от 7.000₽ - Есть другие расцветки! 📍Теги для быстрого поиска: #Nike #Hihg #Blazer Понравилась пара или вещь? Не стесняйся! Напиши нам и мы её привезем в кратчайшие сроки @RolyaSupport

6👍5

Showing the 10 most recent of 10 posts we hold for @faridastorre. 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.

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 6 September 2026 — this entry's latest reading, not the date you are reading this.

“FARIDA STORE” (@faridastorre), 7,739 subscribers as measured 6 September 2026. Telegram Register, tgregister.com/channel/faridastorre.

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.