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Channel

Effer für Wissenschaft

@EFW_inno

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

1,658subscribers

+15 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-1001247194062
TypeChannel
Username@EFW_inno
CreatedBetween 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live18 September 2026
Measurements held13
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/EFW_inno

Topic

Other / unclassifiable — 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 17 September 2026 and assigned it the closest of 31 fixed categories, at 72% 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

1,6431,6591,6516 August 2026 — 1,643 subscribers6 August 2026 — 1,643 subscribers9 August 2026 — 1,644 subscribers12 August 2026 — 1,648 subscribers16 August 2026 — 1,651 subscribers23 August 2026 — 1,654 subscribers25 August 2026 — 1,658 subscribers28 August 2026 — 1,657 subscribers1 September 2026 — 1,659 subscribers4 September 2026 — 1,658 subscribers9 September 2026 — 1,654 subscribers13 September 2026 — 1,655 subscribers18 September 2026 — 1,658 subscribers1,6586 August 202618 September 2026
13 measurements spanning 43 days, net +15. 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 1,641–1,661 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
18 Sept 2026, 04:381,658+3
13 Sept 2026, 13:561,655+1
9 Sept 2026, 15:361,654-4
4 Sept 2026, 07:361,658-1
1 Sept 2026, 05:541,659+2
28 Aug 2026, 20:521,657-1
25 Aug 2026, 23:231,658+4
23 Aug 2026, 00:141,654+3
16 Aug 2026, 19:061,651+3
12 Aug 2026, 22:141,648+4
9 Aug 2026, 11:521,644+1
6 Aug 2026, 18:001,643no change
6 Aug 2026, 08:171,643first reading

Engagement

23 posts held, back to 28 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 pages of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 23 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

19 reactions across 6 posts, in 4 distinct kinds. The most used accounts for 47.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍947.4%
🤣421.1%
315.8%
🤔315.8%

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 6 of the 23 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 19 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 23 most recent posts we hold, published 28 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, 10:13 UTC281 views2 reactionsread 7 August 2026

https://t.me/im_RORIRI/34135 Yes, without a second thought.

👍2

6 Aug 2026, 02:17 UTC151 views3 reactionsread 7 August 2026

这个问题其实以各种形式困扰很多人:是应该怪罪那些使用致瘾产品的人呢,还是应该怪罪那些生产致瘾产品的公司呢? 比如说很容易能够认为这样的观点是有一定道理的:“这种人选择了使用(烟草/酒精/阿片类药物/EA的赌博体育游戏/垃圾食品/etc.etc.etc.),他们的死亡(疾病/贫穷)可能与此有关(直接因为这个),但这是他们的选择。” 但我感觉这种观点和下面的一个比较滑稽的逻辑没什么区别:“A. 母亲选择了生下孩子,B.孩子都是人,C.人都是会死的,D.所以母亲是全世界最大的杀手”,没办法,因为一个人降生确实是这个人死亡最直接的原因,相关性100%。 说到底这不是一个选择不选择的问题,而是一定会有人会被这种带有依赖性的产品吸引,这是人这么多年进化的结果,但瞄着人性的弱点设计的产品却不一定必须存在。

3

6 Aug 2026, 02:08 UTC136 viewsread 7 August 2026

https://www.theexamination.org/articles/deadliest-company-in-the-world

4 Aug 2026, 01:51 UTC195 viewsread 7 August 2026

虽然是个很有意思的initiative,但还是想的太浅。 尤其是所谓的“Privacy-integrity balance”,简直是笑话。如果Privacy被compromise,哪里来的integrity? 而且还是天天抱着一个Governance的想法。信息流行病这个问题既不仅是一个“虚假信息、错误信息”的问题,更不是一个高层次主体就能解决的问题。

4 Aug 2026, 01:48 UTC191 viewsread 7 August 2026

https://unu.edu/publication/misinformation-disinformation-and-crisis-trust-public-institutions-0

Showing the 12 most recent of 23 posts we hold for @EFW_inno. 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.

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 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.

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

“Effer für Wissenschaft” (@EFW_inno), 1,658 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/EFW_inno.

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.