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Created
Between 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Education — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 43% 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
62 measurements spanning 92 days, net +1,052. 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 20,090–21,466 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
7 Nov 2026, 08:47
21,304
-3
6 Nov 2026, 10:16
21,307
+21
5 Nov 2026, 10:08
21,286
+9
4 Nov 2026, 06:29
21,277
+13
3 Nov 2026, 09:17
21,264
+10
2 Nov 2026, 12:51
21,254
+2
1 Nov 2026, 12:16
21,252
+6
31 Oct 2026, 13:28
21,246
+6
30 Oct 2026, 12:17
21,240
+7
29 Oct 2026, 13:44
21,233
+10
28 Oct 2026, 15:50
21,223
+12
27 Oct 2026, 12:19
21,211
+20
26 Oct 2026, 11:14
21,191
+1
25 Oct 2026, 10:20
21,190
-1
24 Oct 2026, 11:46
21,191
+19
23 Oct 2026, 10:46
21,172
+11
22 Oct 2026, 13:46
21,161
+27
21 Oct 2026, 04:21
21,134
+16
20 Oct 2026, 03:35
21,118
+11
19 Oct 2026, 02:56
21,107
first reading
Engagement
183 posts held, back to 1 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 71 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
13.6%
avg views ÷ 21,304 subscribers
Avg views / post
2,890
41 posts measured
Reaction rate
0.205%
reactions ÷ views · ER floor
Posts in window
41
of 183 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
Window
Rolling 30 days · latest post in window 7 November 2026
Posts held
183 (1 August 2026 – 7 November 2026)
Views total
118,550
Reactions total
243
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Nov 2026, 03:03 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
Photos
≈4,030
Links
≈7,520
Lifetime counters from Telegram’s own channel header, read 8 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
841 reactions across 183 posts, in 8 distinct kinds. The most used accounts for 81.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
688
81.8%
👍
69
8.20%
👌
38
4.52%
🔥
19
2.26%
👏
9
1.07%
🤓
9
1.07%
🥰
5
0.595%
🤩
4
0.476%
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 183 of the 183 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 841 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 183 most recent posts we hold, published 1 August 2026 to 7 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: 1 of 41 posts held from the last 30 days (2.44%) 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).
Effectiveness of the Personalised Responses & Integrated Systems for Metabolism on improving insulin resistance among adults with metabolic syndrome: A pilot study (PRISM-I)
by NUS
Description: A 10-week pilot study exploring how personalised lifestyle interventions, supported by wearable devices, may help improve insulin sensitivity.
Duration: 10 weeks, Both lifestyle behavioural interventional study
Requirements…
Investigating Cognitive Flexibility Training
by Nanyang Technological University
Description: We are looking for participants to take part in a study that aims to investigate the effects of cognitive intervention in healthy population.
Duration: Various sessions over 20 days, details in poster, Most sessions will be online except for in-person MRI Scans cognitive testing, cognitive training, questionnaires, mri sca…
Beyond the Label (BTL) Survey
by Beyond the Label (BTL)
Description: Beyond the Label (BTL) is a national movement to address mental health stigma and promote social inclusion for persons with mental health conditions.
Duration: 10-15 minutes, online survey, Online survey
Requirements: Able to complete the survey in English
Compensation: Respondents get a limited edition BRAVE appreciation gift, given on a first-…
Adult Motivation for Continuing Education
by Nanyang Technological University
Description: The study seeks to understand adults' motivation for continuing education.
Duration: 25-30 minutes, Online survey
Requirements: Requirements in poster
Compensation: $10 via PayNow
Participate: tinyurl.com/ACEMS3
#Open till 06 Dec 2026
[IRB Approved]: IRB-2025-875
Follow @sgresearchlobang for more!
Online research study on Singapore English (limited places)
by University of Pennsylvania
Description: Anonymous, online study for Singaporeans 18 and older. Participants will listen to some sentences and provide a simple response about what they heard.
Duration: 10 mins, Online survey
Requirements: Singaporean English speaker aged 18 and older; typical hearing; able to receive PayNow payment; has a laptop, intern…
Survey on E-Commerce Marketplaces
by Forbes Research Pte Ltd
Description: Forbes Research invites individual sellers and businesses to share their views on e-commerce marketplaces, and their own e-commerce platforms
Duration: 30 Minutes - 45 Minutes, Online survey
Requirements: At least one of the following:
1. Involved in the company's e-commerce decisions.
2. Uses or manages the company's e-commerce operations.
…
Measurement of acute metabolite changes following consumption of microalgae drinks
by NUS
Description: Comparing differences in acute metabolite changes after consumption of microalgae drinks in Singapore adults
Duration: 5 study visits (~6 h each), In-person acute randomised controlled trial
Requirements: Refer to poster
Compensation: Up to S$750 for your time, inconvenience, and transportation
Participate: htt…
A Comparative Experiment on Factors Influencing Search Strategies Across Platforms
by Nanyang Technological University
Description: We're conducting a study at Nanyang Technological University (NTU) on how people search for and evaluate information using different tools.
Duration: About 20 minutes, fully online, Online survey
Requirements: Eligibility criteria:
Aged 21+, currently working in Singapore, able to com…
Apartment Simulation Study
by National University of Singapore
Description: You'll visit a model apartment at NUS, watch videos on the computer, answer questions, surveys, wear eye-tracking device for part of the session.
Duration: The whole session is approx. 60 minutes, In-person research survey
Requirements: NUS students aged 18-35 and non-NUS students 21-35; fluent in English; no prior knowledge of signal dete…
Effect of co-consuming different dietary protein sources with salad on the bioavailability of carotenoids
by NUS
Description: To assess the impact of salad co-consumption with different types of proteins on postprandial carotenoid response in Singapore adults.
Duration: 2-3 months, In-person clinical acute trial
Requirements: 21-45 years old (inclusive)
Other requirements in poster
Compensation: $810 for your tim…
Social return on investment (SROI) for expanding mental health screening for youth: Qualitative Interviews
by Duke-NUS Medical School
Description: We are developing a survey to measure suppport for a wellbeing programme. In the interview, you will be asked to provide feedback on the survey.
Duration: 45-60 min, Online interview
Requirements: - Singaporean adult aged 21-65 years old
- Can speak and read English
- W…
Investigating Brain Changes Related to Cognition and Well-Being across the Lifespan
by NUS
Description: To understand brain changes across the lifespan. Study includes 1h brain MRI, blood draw, stool collection, questionnaires, neuropsychological tests.
Duration: 6 weeks, In-person two in-person visits of ~4 hours each at nus medicine, and 1 month of remote daily tracking.
Requirements: 1. No metallic body implant…
❤4👌1
Showing the 12 most recent of 183 posts we hold for @SGResearchLobang. 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.
Posts edited after publishing
@SGResearchLobang edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
28 August 2026
Most recent edit
6 November 2026
Posts recorded as deleted after publishing
We recorded 2 posts on @SGResearchLobang as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
18 August 2026
Most recent seen missing
28 August 2026
Median time before seen missing
4 days
Seen missing in the last 30 days
0
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 25 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
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.
Youth Corps Singapore @YouthCorpsSG · 37,706 Telegram ranks this channel #5 of 33 here — alongside 32 others — read 1 September 2026
Singapore Careers and Job Opportunities - sgCareers @sgCareers · 23,515 Telegram ranks this channel #23 of 72 here — alongside 71 others — read 18 September 2026
Tuition Assignments Singapore - SG Tuition Jobs / SG Tuition Assignments @TuitionAssignmentsSG · 28,734 Telegram ranks this channel #28 of 48 here — alongside 47 others — read 9 September 2026
SG Weekend Plans @sgweekend · 85,917 Telegram ranks this channel #28 of 56 here — alongside 55 others — read 18 August 2026
This channel appears in 4 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“SG Research Lobang 🧑🎓🙋” (@SGResearchLobang), 21,304 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/SGResearchLobang.
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.