https://youtu.be/D6h00CV1LmQ

Channel
Dr.Prof. Stefan Hockertz Original Wissenschaft
@DrProfHockertz
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
25,366subscribers
-23,055 since we began measuring on 9 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002601578091 |
|---|---|
| Type | Channel |
| Username | @DrProfHockertz |
| Created | Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 5 November 2026 |
| Measurements held | 56 |
| Confirmed unchanged | 1 time, most recently 5 November 2026 |
| On Telegram | t.me/DrProfHockertz |
Topic
Politics & activism — 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 93% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Nov 2026, 11:18 | 25,366 | -4 |
| 4 Nov 2026, 07:57 | 25,370 | -4 |
| 3 Nov 2026, 10:17 | 25,374 | +1 |
| 2 Nov 2026, 11:30 | 25,373 | -5 |
| 1 Nov 2026, 14:05 | 25,378 | -6,607 |
| 31 Oct 2026, 15:15 | 31,985 | -10 |
| 30 Oct 2026, 14:46 | 31,995 | -29 |
| 29 Oct 2026, 17:46 | 32,024 | -12,950 |
| 28 Oct 2026, 19:20 | 44,974 | -4,913 |
| 27 Oct 2026, 22:10 | 49,887 | -44 |
| 27 Oct 2026, 00:40 | 49,931 | -38 |
| 25 Oct 2026, 21:20 | 49,969 | +1,298 |
| 24 Oct 2026, 23:48 | 48,671 | +18,736 |
| 23 Oct 2026, 23:59 | 29,935 | -3,060 |
| 22 Oct 2026, 23:36 | 32,995 | -3,487 |
| 21 Oct 2026, 18:46 | 36,482 | -6 |
| 20 Oct 2026, 16:17 | 36,488 | -4 |
| 19 Oct 2026, 18:58 | 36,492 | -1,957 |
| 18 Oct 2026, 21:36 | 38,449 | -2,546 |
| 17 Oct 2026, 18:49 | 40,995 | first reading |
Engagement
581 posts held, back to 7 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 163 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 58.9%
- avg views ÷ 25,366 subscribers
- Avg views / post
- 15,000
- 219 posts measured
- Reaction rate
- 0.058%
- reactions ÷ views · ER floor
- Posts in window
- 219
- of 581 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 52 of 219 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 November 2026 |
|---|---|
| Posts held | 581 (7 August 2026 – 5 November 2026) |
| Views total | 3,274,254 |
| Reactions total | 531 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Nov 2026, 09:25 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
- 12h 28m
- Average length
- 7m 58s
Measured directly from 94 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
1,119 reactions across 151 posts, in 11 distinct kinds. The most used accounts for 34.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 382 | 34.1% | |
| 🔥 | 256 | 22.9% | |
| 👏 | 222 | 19.8% | |
| ❤ | 163 | 14.6% | |
| 💯 | 81 | 7.24% | |
| 👎 | 5 | 0.447% | |
| ⚡ | 4 | 0.357% | |
| 🙏 | 3 | 0.268% | |
| 😢 | 1 | 0.089% | |
| 🤯 | 1 | 0.089% | |
| 🥱 | 1 | 0.089% |
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 154 of the 581 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 1,119 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 581 most recent posts we hold, published 7 August 2026 to 5 November 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
Telegram’s own ‘edited’ marker: 0 of 219 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
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Photo, posted without a caption
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Photo, posted without a caption
Showing the 12 most recent of 581 posts we hold for @DrProfHockertz. 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
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
Names
Channels on the register whose handles appear in this channel's posts.
@VereinWIR · 16,22326 postsAUFWACHKANAL ❗️ deine rote Pille
@Aufwachkanal_deine_rote_Pille · 82,70216 postsProf.Dr.Stefan Hockertz Original Wissenschaft
@ProfHockertz · 54,20314 postsReport24.news
@report24news · 47,46410 postsUncut-News.ch "Das Original"🇨🇭Unabhängige Analysen und Informationen zu Geopolitik, Wirtschaft, Gesundheit, Technologie
@uncut_news · 102,12010 postsStandPunkt
@standpunkt · 4,8389 postsEva Herman Offiziell
@EvaHermanOffiziell · 188,1355 postsImpfen DOKU 🎬
@Impfen_DOKU · 33,7955 postsBITTEL TV - EINFACH ANDERS
@bitteltv · 91,1064 postshenning rosenbusch - Channel
@rosenbusch · 71,6104 postsAktuell360 (Antiilluminaten TV)
@antiilluminaten · 89,8672 postsAUF1
@auf1tv · 272,1122 postsDiene dem Leben
@DieneDemLeben · 18,2012 postsLauraAboli
@LauraAbolichannel · 165,6922 postsWelt der Bilder 📸
@Welt_der_Bilder · 3,0452 postsÄrztlicher Berufsverband Hippokratischer Eid
@Aerzte_hippokratischer_Eid · 6,3221 postTransition News
@CoronaTransition · 12,7241 postBÜCHER + KRISENVORSORGE + NATURPRODUKTE
@derbuechershop · 7,0141 postimpfen-nein-danke.de offiziell | Vorsprung durch Wissen
@impfen_nein_danke · 12,2951 postJUNGE TAT
@Jungetat · 9,0891 post❤️ paragrafen/dschungel Info und was thun 18. Januar 2022 ❤
@parageaf513dschungel · 10,5731 postProf.Dr.Stefan Hockertz Original
@ProfStefanHockertz · 1,0041 postSören Schumann - Gesundheit Ganzheitlich
@soeren_schumann · 59,9621 postStefan Magnet
@stefanmagnet · 68,1511 post
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@DrProfHockertz named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 2 posts, 23 October 2026 – 24 October 2026
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 5 November 2026 — this entry's latest reading, not the date you are reading this.
“Dr.Prof. Stefan Hockertz Original Wissenschaft” (@DrProfHockertz), 25,366 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/DrProfHockertz.
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.