Telegram RegisterThe public register of Telegram

Channel

Critical thinking

@feedbrain

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

14,523subscribers

-36 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001105427255
TypeChannel
Username@feedbrain
DescriptionContacts ✉️ @penalty Navigation: #CognitiveBiases #Psychology #Books #LogicalFallacy #Explanations
Created26 February 2017measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/feedbrain

Growth

14,52314,55914,5416 August 2026 — 14,559 subscribers6 August 2026 — 14,559 subscribers6 August 2026 — 14,558 subscribers7 August 2026 — 14,555 subscribers9 August 2026 — 14,546 subscribers10 August 2026 — 14,539 subscribers11 August 2026 — 14,530 subscribers12 August 2026 — 14,523 subscribers6 August 202612 August 2026
8 measurements spanning 7 days, net -36. 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 14,518–14,564 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 21:5314,523-7
11 Aug 2026, 18:2314,530-9
10 Aug 2026, 16:5814,539-7
9 Aug 2026, 17:0514,546-9
7 Aug 2026, 12:4014,555-3
6 Aug 2026, 11:1014,558-1
6 Aug 2026, 02:2214,559no change
6 Aug 2026, 01:5014,559first reading

Engagement

20 posts held, back to 15 April 2021the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof 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 20 posts for this entry, the most recent from 18 December 2025. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Photos
5
Links
61

Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

2,747 reactions across 20 posts, in 27 distinct kinds. The most used accounts for 65.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍1,79465.3%
48717.7%
🔥1806.55%
👏411.49%
🤔351.27%
🐳260.946%
🙏240.874%
😱230.837%
💯220.801%
👌180.655%
👎180.655%
🥰160.582%
😁140.51%
😢120.437%
🆒50.182%
🤯50.182%
40.146%
💩40.146%
30.109%
👻30.109%
7 further kinds130.473%

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 20 of the 20 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 2,747reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 15 April 2021 to 18 December 2025, 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

18 Dec 2025, 15:52 UTC≈6,550 views72 reactionsread 13 August 2026

False premise A false premise is a mistaken starting assumption. You can build a long chain of reasoning where every step is logically correct, yet the argument is still unsound—because it inherits that original mistake. Example (false premise): “For any two people, the one who talks more during a conversation is more knowledgeable about the topic.” Follow it logically and you get: the most talkative person is the

49👍17👏2❤‍🔥1👎1💩1🔥1

11 Jun 2025, 10:44 UTC≈10,300 views88 reactionsread 13 August 2026

Ben Franklin effect (reading time – 50 sec.) The Ben Franklin effect is a proposed psychological phenomenon: a person who has already performed a favor for another is more likely to do another favor for the other than if they had received a favor from that person. An explanation for this is cognitive dissonance. People reason that they help others because they like them, even if they do not, because their minds str

👍5223🔥7🤯4👎2

8 Aug 2024, 15:34 UTC≈17,700 views81 reactionsread 13 August 2026

Knew-It-All-Along Phenomenon It's the common tendency for people to perceive past events as having been more predictable than they were The phenomenonis more likely to occur when the outcome of an event is negative rather than positive. This is a phenomenon consistent with the general tendency for people to pay more attention to negative outcomes of events than positive outcomes. Financial bubbles are often heavil

👍5412🔥63👎3💔2🥰1

24 Jul 2024, 07:48 UTC≈17,600 views77 reactionsread 13 August 2026

Endowment effect The endowment effect, also known as divestiture aversion, is the finding that people are more likely to retain an object they own than acquire that same object when they do not own it. One of the most famous examples of the endowment effect in the literature is from a study by Daniel Kahneman, Jack Knetsch & Richard Thaler,[4] in which Cornell University undergraduates were given a mug and then off

43👍20🔥6🆒5🥱2🤯1

8 Feb 2024, 08:26 UTC≈24,400 views161 reactionsread 13 August 2026

Impostor Phenomenon (reading time – 30 sec.) Impostor phenomenon, or impostor syndrome, is a psychological phenomenon where individuals doubt their abilities and fear being exposed as frauds, despite evidence of their competence. Those experiencing it often attribute their achievements to luck or deception, downplay their skills, and dismiss positive feedback. This phenomenon is not limited by demographics and can

85👍55🔥12🙏6👏2👌1

26 Jan 2024, 07:20 UTC≈23,600 views130 reactionsread 13 August 2026

Belief Perseverance (reading time – 30 sec.) Belief perseverance refers to the tendency of people to cling to their existing beliefs even when presented with evidence that contradicts those beliefs. In other words, individuals may continue to maintain their initial beliefs despite encountering information that challenges or disconfirms those beliefs. This phenomenon can be powerful and persistent because people oft

👍8426🔥9😢6👏3😁2

22 Feb 2023, 16:36 UTC≈42,600 views288 reactionsread 13 August 2026

Hindsight Bias (reading time – 30 sec.) Hindsight bias is the tendency to believe, after an event has occurred, that one would have predicted or expected the outcome. For example, after a sports team wins a championship, fans and analysts may claim they knew the team would win all along, even if they didn't actually have that level of confidence before the event took place. Another example is a stock market investo

👍19831🔥16💯15👌9🙏54👏4

12 Feb 2023, 10:33 UTC≈39,600 views230 reactionsread 13 August 2026

Curse of Knowledge (reading time – 40 sec.) The curse of knowledge bias occurs when individuals assume that others have the same level of understanding or knowledge as they do. For instance, a teacher may assume that all of their students understand a concept that was just taught, when in reality some students are still struggling to grasp the idea. Another example is a technical expert who is unable to explain a c

👍153🔥3024👏12😢6👎2👀1💯1

2 Feb 2023, 16:26 UTC≈34,500 views163 reactionsread 13 August 2026

Default Effect (reading time – 30 sec.) One example of the default effect cognitive bias is when individuals are more likely to choose the option that is set as the default in a decision-making scenario. For instance, when signing up for a new service, if opting-in to a certain feature is set as the default, people are more likely to go along with it and not change the setting, even if they might have preferred a di

👍12818💯6😁4🤩3👌2🙏2

4 Dec 2022, 08:34 UTC≈38,000 views261 reactionsread 13 August 2026

Halo Effect (reading time – 30 sec.) The halo effect is a type of cognitive bias in which our overall impression of a person influences how we feel and think about their character. Essentially, your overall impression of a person ("He is nice!") impacts your evaluations of that person's specific traits ("He is also smart!"). Perceptions of a single trait can carry over to how people perceive other aspects of that pe

👍17839🔥10🤔8😱6👌5🥰4👻3

25 Jun 2022, 10:00 UTC≈44,600 views367 reactionsread 13 August 2026

Fundamental Attribution Error (reading time – 20 sec.) The fundamental attribution error (FAE) describes how, when making judgments about people’s behavior, we often overemphasize dispositional factors and downplay situational ones.5 In other words, we believe that people’s personality traits have more influence on their actions, compared to the other factors over which they don’t have control. Let’s say you’re dri

👍24250🐳26🤔15👏9🔥8😁5😱4

2 May 2022, 09:38 UTC≈43,300 views229 reactionsread 13 August 2026

Apophenia (reading time – 20 sec.) Apophenia is the tendency to perceive meaningful connections between unrelated things For example, gamblers may imagine that they see patterns in the numbers that appear in lotteries, card games, or roulette wheels, where no such patterns exist. A common example of this is the gambler's fallacy. Topic: #CognitiveBiases Source: www.wikipedia.org

👍17926🔥15👎4🤔3🙏2

Showing the 12 most recent of 20 posts we hold for @feedbrain. 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 — 1,077,980 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.

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.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Critical thinking” (@feedbrain), 14,523 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/feedbrain.

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.