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Channel

Рекомендации, Поиск и Путешествия

@Recsys_IR_Travel

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

1,214subscribers

+3 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-1002344991607
TypeChannel
Username@Recsys_IR_Travel
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/Recsys_IR_Travel

Growth

1,2111,2141,212.56 August 2026 — 1,211 subscribers7 August 2026 — 1,211 subscribers10 August 2026 — 1,214 subscribers6 August 202610 August 2026
3 measurements spanning 3 days, net +3. 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 1,211–1,214 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 04:381,214+3
7 Aug 2026, 04:531,211no change
6 Aug 2026, 18:181,211first reading

Engagement

13 posts held, back to 11 March 2026the 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
113.6%
avg views ÷ 1,214 subscribers
Avg views / post
1,380
3 posts measured
Reaction rate
1.52%
reactions ÷ views · ER floor
Posts in window
3
of 13 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 5 August 2026
Posts held13 (11 March 20265 August 2026)
Views total4,137
Reactions total63
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 18:18 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

235 reactions across 13 posts, in 5 distinct kinds. The most used accounts for 80.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥19080.9%
👍3314.0%
62.55%
🎉41.70%
🥰20.851%

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 13 of the 13 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 235reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 11 March 2026 to 5 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

5 Aug 2026, 08:41 UTC368 views11 reactionsread 6 August 2026

RecSys опубликовали список принятых статей! Посмотреть можно тут: recsys.acm.org/recsys26/contributions/ Уже успел пробежаться по авторам и увидел несколько знакомых имён, в том числе ребят из нашего чата! 🎉 Примите искренние поздравления, отличный результат! Жаль, конечно, что в этом году не указали affiliations — отбирать статьи по топовым компаниям и лабам теперь чуть сложнее. 👇 Делитесь в комментариях: что уж

🔥11

Signed Sasha Petrov

29 Jul 2026, 07:53 UTC709 views41 reactionsread 6 August 2026

Ну все, я теперь официально индустриальный рисерчер! 🟢 Мою с коллегами статью (Full Paper) приняли на Industry track ACM RecSys 2026! 📌 Hypothesis-Driven Shelf Generation for Personalised Recommendation 🔗 https://arxiv.org/pdf/2607.25823 В работе делимся тем, как мы меняем подход к формированию Spotify Home. Мы разработали систему, которая заменяет классические захардкоженные шаблоны полок рекомендаций на natural-

🔥37🎉4

Signed Sasha Petrov

21 Jul 2026, 09:44 UTC≈3,060 views11 reactionsread 6 August 2026

USRW 2026: Call for Papers — дедлайн продлён до 27 июля 🔎 Это тот самый Unified Search and Recommendation Workshop, который я недавно упоминал в посте про мои воркшопы на RecSys. Теперь можно наконец рассказать подробнее: мы опубликовали программу и открыли приём статей. Для меня это первый опыт организации отдельного воркшопа — и особенно приятно, что он посвящён теме, вокруг которой, собственно, и строится этот к

5👍3🔥3

Signed Sasha Petrov

9 Jun 2026, 08:10 UTC953 views27 reactionsread 6 August 2026
Photo

Бонус работы в Spotify: на корпоративах тут выступают артисты мировой величины. На прошлой неделе летал в Стокгольм праздновать день рождения компании. Масштаб, мягко говоря, поражает. Судите сами, среди хедлайнеров: • 👑 Karol G — главная латиноамериканская певица прямо сейчас. • ⚡️ Travis Scott — абсолютный топ в мировом рэпе. • 🎹 Swedish House Mafia — а это отдельный вид кайфа для таких фанатов EDM, как я! И это

🔥24🥰2👍1

Signed Sasha Petrov

14 May 2026, 08:59 UTC≈1,060 views23 reactionsread 6 August 2026

Еще новости с РекСиса — рексис принял наш туториал: Title: Transformer-based Sequential Recommender Systems Instructors: Jan Malte Lichtenberg, Aleksandr V. Petrov Transformer-based models have become the cornerstone of sequential recommendation, yet they are often perceived either as rigid engineering recipes or as a collection of disconnected architectures. This tutorial demystifies these systems by centering on

🔥18👍5

Signed Sasha Petrov

29 Apr 2026, 14:03 UTC≈1,140 views5 reactionsread 6 August 2026

RecSys опубликовали список воркшопов: https://recsys.acm.org/recsys26/workshops/ Мои ворокшопы в первый (FRAME) и последний день конференции (USRW)

👍5

Signed Sasha Petrov

23 Apr 2026, 09:31 UTC732 views3 reactionsread 6 August 2026

Статья от коллег из Spotify. Основная часть работы была сделана до того как я присоединился, поэтому меня в авторах тут нет, но в целом из статьи можно примерно понять чем мы тут занимаемся.

👍3

Signed Sasha Petrov

23 Apr 2026, 09:31 UTC≈1,000 views9 reactionsread 6 August 2026
Forwarded from @RecSysChannelPhoto

A Unified Language Model for Large Scale Search, Recommendation, and Reasoning В сегодняшней статье Spotify представляют NEO — унифицированную модель decoder-only, которая работает с гетерогенными данными (текст и рекомендательные объекты). При этом она должна удовлетворять жёстким требованиям к качеству выдачи и латентности. Традиционные рекомендательные системы, несмотря на доказанную эффективность на больших объ

🔥81

Signed Sasha Petrov

3 Apr 2026, 08:22 UTC≈1,010 views19 reactionsread 6 August 2026

Сразу два воркшопа на ACM RecSys 2026! 🚀 В этом году пробую себя в новой роли: вхожу в оргкомитет сразу двух воркшопов на главной конференции по рекомендательным системам. Темы находятся на стыке поиска, рекомендаций и методологии экспериментов. Коротко о том, что готовим: 1️⃣ Unified Search and Recommendation Workshop (2 октября) Мы верим, что разделение поиска и рекомендаций - скорее исторический артефакт. С поя

🔥19

Signed Sasha Petrov

31 Mar 2026, 09:26 UTC875 views4 reactionsread 6 August 2026

В комментах спросили про то какие критерии "на best reviewer". Ответа конкретно про ECIR я не знаю, но могу поделиться слайдами про то как писать ревью 😊 Эти слайды подготовили Olivier Jeunen & Christine Bauer специально для ревьюеров конференции RecSys 2025 (хотя основные принципы применимы для любой конференции). Для рядовых ревьюеров (PC Member): https://christinebauer.eu/pdfs/recsys2025_review_guidelines.pdf Дл

👍2🔥2

Signed Sasha Petrov

30 Mar 2026, 09:21 UTC790 views23 reactionsread 6 August 2026
Photo

До ECIR я в этом году не добрался, но Reviewer Award получил 😊

👍14🔥9

Signed Sasha Petrov

26 Mar 2026, 17:13 UTC≈1,070 views36 reactionsread 6 August 2026
File

Двойной юбилей на Google Scholar сегодня: H-Index добрался до 10, а самая цитируемая статья набрала 100 цитирований. Кто-то мне говорил что в DeepMind без H-index 10 не берут, так что теперь можно 😂

🔥36

Signed Sasha Petrov

Showing the 12 most recent of 13 posts we hold for @Recsys_IR_Travel. 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 — 85,314 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 3 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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Рекомендации, Поиск и Путешествия” (@Recsys_IR_Travel), 1,214 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/Recsys_IR_Travel.

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.