Jean-Baptiste Lefevre engagement report
@jblefevre60 - 94K followers on X
Measured over 8 original posts from a 30-day window, last computed on August 25, 2026.
Engagement
A typical post picks up 112 interactions against 94K followers, an engagement rate of 0.119%. Measured over 8 original posts, its engagement rate beats 54% of 4,347 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 10K times each, and 1.11% of those impressions turn into an interaction. That is about 10.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.1 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 05:00 UTC, and Wednesday is the busiest day of the week. Of the 8 posts sampled, 100% carry an image or video and 50% link out. The account's strongest tracked post pulled 19K interactions, about 172x its own typical post. Recurring topics include #ai, #machinelearning, #datascience.
Measured over 8 original posts from a 30-day window, last computed on August 25, 2026. Recurring tags: #ai, #machinelearning, #datascience.
Compared with accounts its own size
Jean-Baptiste Lefevre's engagement rate beats 54% of the tracked X accounts closest to it in follower count (4,347 accounts, accounts of similar size (decile 5 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 49% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.119%, Jean-Baptiste Lefevre sits above the 50th percentile of the 41,976 accounts in this comparison. That places it in the above the median band, which runs 0.083% to 0.448%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.013% |
| 50th percentile | 0.083% |
| 75th percentile | 0.448% |
| 90th percentile | 2.08% |
| 99th percentile | 142.9% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 05:00 UTC, and Wednesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 59K |
| 01:00 UTC | -2% | 60K |
| 02:00 UTC | -4% | 58K |
| 03:00 UTC | -4% | 62K |
| 04:00 UTC | -6% | 50K |
| 05:00 UTC | -5% | 49K |
| 06:00 UTC | -5% | 56K |
| 07:00 UTC | -5% | 61K |
| 08:00 UTC | -4% | 71K |
| 09:00 UTC | -4% | 82K |
| 10:00 UTC | -3% | 84K |
| 11:00 UTC | -3% | 91K |
| 12:00 UTC | -2% | 100K |
| 13:00 UTC | -2% | 110K |
| 14:00 UTC | -3% | 113K |
| 15:00 UTC | -2% | 117K |
| 16:00 UTC | -3% | 114K |
| 17:00 UTC | -3% | 106K |
| 18:00 UTC | -2% | 99K |
| 19:00 UTC | -2% | 93K |
| 20:00 UTC | -1% | 87K |
| 21:00 UTC | -1% | 77K |
| 22:00 UTC | -2% | 67K |
| 23:00 UTC | -1% | 60K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 257K |
| Monday | +1% | 329K |
| Tuesday | -2% | 355K |
| Wednesday | -4% | 323K |
| Thursday | -3% | 273K |
| Friday | -3% | 277K |
| Saturday | +3% | 250K |
Best tweets
- Jul 20, 2026172x their median
The purpose of art was once not to shock or transgress, but to elevate the soul. https://t.co/YYyUktamR3
- Jun 6, 2026129x their median
A Russian psychologist spent 10 years proving that the act of talking to yourself out loud is one of the most powerful cognitive tools the human brain has, and almost nobody outside his field has read the work. His name was Lev Vygotsky. He worked in Moscow in the 1920s and died of tuberculosis in 1934 at the age of 37. He had no laboratory, no funding, almost no English readers, and a body of work that the Soviet government suppressed for two decades after he died. He produced the foundational theory of how human cognition actually develops, and the central piece of that theory was a behavior almost every adult is faintly embarrassed about. Vygotsky noticed that young children talk to themselves constantly. They narrate their own actions, they argue with imaginary opponents, they instruct themselves through tasks out loud. The dominant theory at the time, from the Swiss psychologist Jean Piaget, said this was a sign of cognitive immaturity that children would eventually grow out of as they learned to think properly. Vygotsky said the exact opposite. He argued that this self-directed speech was the most important cognitive event in the entire developmental window, because it was the moment a child first started to use language as a tool to control their own mind. The child was not failing to think. The child was learning how to think by externalizing the process and listening to themselves do it. He predicted that as children matured, this out-loud self-talk would not disappear. It would go underground. It would become silent inner speech, which is the running monologue every adult has inside their own head for the rest of their life. The voice you hear when you read this sentence is the direct descendant of a four-year-old narrating their own block tower. For 50 years almost nobody outside Russia had access to his work, and the few researchers who did pick it up could not get funding to test it. Then in the early 2000s the experiments finally started to pile up, and what they found was that Vygotsky had been right about something even more important than he knew. The first major study came from Gary Lupyan at the University of Wisconsin and Daniel Swingley at the University of Pennsylvania in 2012. They ran a simple visual search experiment. Participants were shown 20 images at once and asked to find a specific object, like a banana or a chair. In one condition they searched silently. In the other condition they were told to say the name of the object out loud to themselves while looking for it. The participants who spoke the target name out loud found the object significantly faster, with higher accuracy, than the participants who searched in silence. The effect was strongest when the spoken word matched a familiar object the brain already had a strong category for. Saying the word out loud literally tuned the visual system to detect that thing better. The researchers called it the label feedback effect, and the implication was that the act of vocalizing a goal physically changes how the brain processes the world while pursuing it. The second major study came out of the University of Michigan and Michigan State in 2017. The lead researchers were Ethan Kross and Jason Moser, and they used both EEG and fMRI to record what happens inside the brain when people talk to themselves while emotionally upset. They asked participants to recall painful autobiographical memories and reflect on them in two different ways. Some used the first person, saying things like "why am I feeling this way." Others used the third person, referring to themselves by their own name, saying things like "why is John feeling this way." The brain scans showed that the simple act of switching from first person to third person, even silently, decreased activity in the medial prefrontal cortex, the region responsible for rumination and self-referential pain. Within a single second of using their own name instead of the word I, participants showed measurably lower emotional reactivity. The shift required no extra cognitive effort. It cost the brain nothing. And it worked. Kross described the mechanism in his interviews. Talking to yourself by name creates a small amount of psychological distance from your own experience. Your brain processes the situation more like a problem belonging to someone else, which means it can analyze it instead of drowning in it. What Vygotsky had intuited in 1934 turned out to be even more powerful than the developmental theory he built it into. The voice you use to talk to yourself is not background noise. It is one of the most precise cognitive tools the brain has, and you can change how it works just by changing the pronoun you use. People who talk through problems out loud are not anxious or unstable. They are running an externalized version of a process the rest of us are running silently and worse. The kindergartener narrating their block tower, the surgeon muttering through a procedure, the engineer pacing a hallway describing a bug to nobody, the athlete repeating a cue to themselves before a free throw, they are all using the same ancient mechanism that builds and steers human thought. You can run the experiment yourself the next time you are stuck on something hard. Stop trying to solve it silently in your head. Say it out loud. Describe what you are seeing. Walk yourself through the steps as if you were explaining it to a colleague who is not in the room. And when something genuinely upsets you, switch to your own name. Ask why this person is feeling this way, instead of why I am feeling this way. The voice you have been told to keep quiet your entire life is one of the oldest pieces of cognitive technology you own. Most people are still embarrassed to use it.
- Jul 28, 202682x their median
ALERT IN EUROPE! Fires in Spain and France have merged into a MEGAFIRE. More than 60 cities have already been evacuated. ⚠️ https://t.co/8GBtNdVndP
- Aug 5, 20269.8x their median
Remembering one of the most powerful and distinguished storytellers of our time: Toni Morrison. She became the first African American woman to be awarded a #NobelPrize when she received the literature prize in 1993. Learn more: https://t.co/eKJTEpQoMb https://t.co/2nY2Bvz9Yw
- Jan 16, 20219.4x their median
[#CES2021] Social media review, brands and Influencers! #AI #MachineLearning #Robotics #5G #IoT @visibrain https://t.co/7pzKi7UpMs @ValaAfshar @Analytics_699 @HaroldSinnott @EvanKirstel @ipfconline1 @Nicochan33 @Fabriziobustama @mvollmer1 @PawlowskiMario @MargaretSiegien https://t.co/XtgjFAUCXa
- Aug 18, 20268.1x their median
The Thinking Tree. An ancient 3000 years-old Olive tree in Puglia, Italy 🇮🇹 https://t.co/k9O6y2xMta
- Jul 25, 20267.4x their median
Thank You 🙏. Two simple words that mean so much. This is Japanese culture—saying thank you in this way. I really love it 💝 https://t.co/IB3jNEc4rT
- Jun 15, 20265.0x their median
New neurological research reveals that writing by hand activates complex brain networks critical for learning and memory, while typing on a keyboard effectively lets the brain coast on autopilot. For over two decades, Norwegian neuroscientist Audrey van der Meer has studied how handwriting shapes the human brain. In a landmark 2024 study published in Frontiers in Psychology, her team utilized high-density EEG caps to track the brain activity of students as they either handwrote with a digital pen or typed on a keyboard. The results were stark: writing by hand triggered a synchronized burst of neural activity across the entire brain, connecting regions responsible for memory, sensory integration, and active learning. Conversely, when students typed the exact same words, this sophisticated cognitive network collapsed. Because typing relies on repetitive, identical keystrokes, it requires minimal spatial problem-solving, leaving crucial learning centers in the brain quiet and disengaged. This neurological difference directly impacts how we process and retain information. Earlier research by Pam Mueller and Daniel Oppenheimer at Princeton University mirrored these findings, demonstrating that students taking longhand notes consistently outperformed laptop-users on conceptual comprehension tests. While laptop users transcribe lectures verbatim without processing the information, handwriting forces students to listen critically, synthesize ideas, and summarize concepts in real time. Our brains are part of an embodied, living system. By replacing physically rich activities with frictionless digital keystrokes, we secure quick surface-level efficiency at the cost of deep cognitive engagement. To truly process information, make better decisions, and keep our minds sharp, the simplest solution is also the most ancient: pick up a pen. source: van der Meer, A. L. H., & van der Weel, F. R. R. (2024). Handwriting but not typewriting leads to widespread brain connectivity. Frontiers in Psychology, 14, 1219945.
- Aug 6, 2026
A new study asked 272 experts to evaluate AI risks and the sectors that are most vulnerable over the next five years. Learn more: https://t.co/0Eq7ES0QiY https://t.co/KGXWOgZmQo
- Aug 10, 2026
Ever saw weird ads online? With the Digital Services Act: ✅Ads must be clearly labelled 🚫Minors cannot be targeted 🚫Special categories of personal data are forbidden Discover your online rights: https://t.co/OAUDfJ5Amp #DSA https://t.co/VpGaXDwDVP
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 112 interactions against 94K followers, an engagement rate of 0.119%. Measured over 8 original posts, its engagement rate beats 54% of 4,347 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 10K times each, and 1.11% of those impressions turn into an interaction. That is about 10.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.1 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 05:00 UTC, and Wednesday is the busiest day of the week. Of the 8 posts sampled, 100% carry an image or video and 50% link out. The account's strongest tracked post pulled 19K interactions, about 172x its own typical post. Recurring topics include #ai, #machinelearning, #datascience.
- What is Jean-Baptiste Lefevre's engagement rate on X?
- Jean-Baptiste Lefevre (@jblefevre60) has an engagement rate of 0.119%, based on the median interactions across 8 original posts from the last 30 days against 93,949 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.119%, Jean-Baptiste Lefevre sits above the 50th percentile of the 41,976 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @jblefevre60 have real engagement?
- Its engagement rate beats 54% of the tracked X accounts closest to it in follower count (4,347 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @jblefevre60 post?
- Most posts go out around 05:00 UTC, and Wednesday is its busiest day, at roughly 2.1 posts per day across the measured window.