Channel
@ssgeos_edu
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Referenced elsewhere · Cite this entry
4,908subscribers
+75 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001806300159 |
|---|---|
| Type | Channel |
| Username | @ssgeos_edu |
| Created | Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 13 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/ssgeos_edu |
Science — 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 13 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 15:19 | 4,908 | -3 |
| 14 Sept 2026, 15:21 | 4,911 | +8 |
| 5 Sept 2026, 11:36 | 4,903 | +1 |
| 1 Sept 2026, 07:15 | 4,902 | +2 |
| 26 Aug 2026, 06:53 | 4,900 | +4 |
| 23 Aug 2026, 02:55 | 4,896 | +5 |
| 20 Aug 2026, 01:32 | 4,891 | +13 |
| 17 Aug 2026, 12:17 | 4,878 | +19 |
| 14 Aug 2026, 01:04 | 4,859 | +14 |
| 10 Aug 2026, 22:31 | 4,845 | +8 |
| 8 Aug 2026, 03:57 | 4,837 | +4 |
| 7 Aug 2026, 13:47 | 4,833 | no change |
| 7 Aug 2026, 13:39 | 4,833 | first reading |
19 posts held, back to 18 April 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 7 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 19 posts for this entry, the most recent from 3 August 2026. An engagement rate over an empty window would be a number about nothing.
524 reactions across 19 posts, in 12 distinct kinds. The most used accounts for 55.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 289 | 55.2% | |
| ❤ | 101 | 19.3% | |
| 👀 | 55 | 10.5% | |
| 🙏 | 45 | 8.59% | |
| 👏 | 9 | 1.72% | |
| 😢 | 8 | 1.53% | |
| 🕊 | 6 | 1.15% | |
| 💔 | 4 | 0.763% | |
| 😱 | 3 | 0.573% | |
| 🤔 | 2 | 0.382% | |
| 🔥 | 1 | 0.191% | |
| 😴 | 1 | 0.191% |
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 19 of the 19 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 524 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 18 April 2025 to 3 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.
The repo has been updated with all M ≥ 8.5 events from the GEM-GHEC catalog and a peer-reviewed paper (->1361). With this update the p-value dropped from 0.028 to 0.008. Stats regarding phase preference were also added, showing an obvious preference for Full Moons. https://github.com/ssgeos/great-earthquakes-lunar-phase-statistics
👍9❤4🙏1
We published new statistics about the largest earthquakes (M≥8.5) in history and lunar phases. Dr. Susan Hough's 2018 paper is correct for a M ≥ 8.0 threshold (random occurrence), but with rising magnitude a shift is observed towards the 4 phases! https://github.com/ssgeos/great-earthquakes-lunar-phase-statistics
👍8👏3❤2👀2
M 7.8 EARTHQUAKE PHILIPPINES | SEISMIC UNREST LIKELY TO CONTINUE | 10 DAYS OVERVIEW https://www.youtube.com/watch?v=p9P1znyeipc
👀7😢5👍2🤔2🙏2
A significant seismic increase occurred from 20 to 26 March 2026, counting eight M 6+ earthquakes, three of which M 6.5+ peaking M 7.5 on the 24th. Typical temporal clustering aligning with converging planetary and lunar geometry, whereby the Moon is the most significant seismic modulator.
👍17❤4😱3🙏2😴1
The usual clustering of stronger (M≥5.5) #earthquakes from 5-14 February occurred almost symmetrically with the geometric peaks that we discussed when this time-frame commenced. These seismic bursts demonstrate seismic modulation related to planetary and lunar geometry.
👀12❤6👍1🔥1
According to a 2019 study (see link) the Eastern Mediterranean region has been affected by 10 Extreme Water Events (EWE) or tsunamis from large earthquakes along the Hellenic Arc and Santorini eruptions in the last 7500 years. This implies an average ~750 years recurrence interval. The youngest EWE occurred in 365 AD, which is almost 1700 years ago. These EWEs do not just impact Crete's coastal areas, but the entire…
👀9❤6👍4
Thus far in this time-frame (31 December - 8 January) three temporal #earthquake clusters occurred matching the #lunar (green) peaks (as anticipated). Strongest event thus far was the M 6.5 Mexico tremor at Full Moon.
👍17❤2👀1
While mainstream consensus traditionally claims that planetary/lunar tides have little/no influence on seismic activity, more recent peer-reviewed studies challenge the paradigm, some directly confirming our own research results. Here we list four valuable papers worth reading: 1. Artificial Intelligence for Assessing the Planets' Positions as a Precursor to Earthquake Events (El Moudden et al., 2024) https://www.sc…
❤25👍5
One of the biggest problems in earthquake risk countries is the weakness of unreinforced masonry (URM) and reinforced concrete (RC) buildings. As an example we list the Mediterranean countries Italy, Greece and Turkey. Italy: ~70–80% pre-modern codes; heavy reliance on vulnerable URM in historic/rural areas. Greece: ~80% of buildings pre-1985 code; many low-rise masonry/RC in urban and island villages. Turkey: Lar…
❤22👍13
The three lunar peaks (green) on the SSGI-graph since the 21st, each show tight temporal clustering of stronger (M≥5.5) earthquakes, with each cluster peaking M6 (M 6.5, M 6.0 and M 6.6 respectively).
👍19👀1
Mercury's 60,000-Year Tight Sequence with Saturn and Neptune https://www.youtube.com/watch?v=_sVDaArZVy4
👍28❤10👀2
In this time-frame clustering of stronger (M ≥ 5.5) #earthquakes occurred primarily after lunar peaks (green). The largest #earthquake was M 6.5 near the north coast of New Guinea, P.N.G. on the 20th. #SSGI
🙏17👀12👍6🕊6❤5
Showing the 12 most recent of 19 posts we hold for @ssgeos_edu. 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.
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.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
This handle named by sources this register does not control and did not measure — each shown exactly as found, attributed by name, dated to when it was read.
Hacker News
This handle was named once in a Hacker News comment or story, via the public Algolia search API. HN comment and story text has no confirmed reuse licence, so nothing quoted from either is reproduced here — only that a mention exists, when, and by whom, with a link to read it at the source.
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.
“SSGEOS Research and Education” (@ssgeos_edu), 4,908 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/ssgeos_edu.
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.