Vijay Shekhar Sharma engagement report
@vijayshekhar - 924K followers on X
Measured over 26 original posts from a 30-day window, last computed on October 28, 2026.
Engagement
A typical post picks up 870 interactions against 924K followers, an engagement rate of 0.094%. Measured over 26 original posts, its engagement rate beats 69% of 21,624 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 127K times each, and 0.682% of those impressions turn into an interaction. That is about 13.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 06:00 UTC, and Wednesday is the busiest day of the week. Of the 26 posts sampled, 92% carry an image or video and 12% link out. The account's strongest tracked post pulled 36K interactions, about 42x its own typical post. Recurring topics include #dpupdates, #gujaratpolice.
Measured over 26 original posts from a 30-day window, last computed on October 28, 2026. Recurring tags: #dpupdates, #gujaratpolice.
Compared with accounts its own size
Vijay Shekhar Sharma's engagement rate beats 69% of the tracked X accounts closest to it in follower count (21,624 accounts, accounts of similar size (decile 10 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 37% 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 0.094%, Vijay Shekhar Sharma sits above the 25th percentile of the 218,065 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.149%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.149% |
| 75th percentile | 0.705% |
| 90th percentile | 2.63% |
| 99th percentile | 82.6% |
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 06:00 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% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 92% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 12% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 92% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 12% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 371 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Oct 19, 202642x their median
CISF’s Swift Response: Suspicious Person Apprehended While Attempting to Escape at Metro Station! Alert CISF personnel at Jama Masjid Metro Station of DMRC sprang into action when a passenger attempted to flee after a suspicious, dense object appeared on the XBIS screen during baggage screening. Demonstrating quick reflexes and effective coordination, CISF personnel immediately pursued and apprehended the fleeing passenger near the exit gate. Further examination of his belongings revealed an unidentified semi-solid substance concealed in a stitched portion of his undergarment. The passenger, who claimed to be an NRI residing in Kuala Lumpur, along with his belongings, was handed over to the police for further investigation. The swift action and alertness of CISF personnel highlight their prompt response and commitment to ensuring metro security. #CISF #MetroSecurity #Vigilance #QuickResponse @HMOIndia @PIB_India @CISF_Delhimetro
- Oct 23, 202618x their median
China influenced, Pakistani infiltrated, brown sepoys staffed Bloomberg is asking why India is building amazing expressways like the US. I see this news with concern. This news by this media for me means DS is going to influence & instigate Truckers into protests blocking freeways to hit India's logistics, economy, and halt freeway construction. They are building public support for it at the earnest. Beware.
- Jul 25, 202663x their median
On this auspicious day of Ashada Ekadashi, I am very happy to announce the launch of my humble attempt to make history interesting. https://t.co/SGfD2ebBpO The idea is actually very very simple You go to the site, select a year, and It will show you who ruled which part of India at that point in time.
- Aug 21, 202615x their median
Make more in India! 🇮🇳 https://t.co/r5N3P5B8ty
- Oct 13, 202613x their median
What if Spotlight actually understood the meaning inside your files? DigUp is an open-source macOS menu bar app powered by EmbeddingGemma 2 that brings 100% local, multimodal semantic search to your Mac. Instead of searching for file names, you can use natural language to: 📸 Find specific scenes in your photos ⏳ Jump to the exact timestamp in audio or video 💻 Search through your codebase by intent Everything runs locally in a single vector space.
- Oct 17, 202611x their median
Perfect reply to Elon’s flying car by Bugatti’s CEO. https://t.co/TP56kfLEMz
- Sep 16, 20269.3x their median
JUST IN: Co-inventor of ChatGPT launches new AI startup which claims to be up to 200x faster, plans to forever charge $0 for output tokens.
- Oct 24, 20269.2x their median
As India braces for Delhi - Mumbai "pollution season" and accompanied protests (we can all predict this), do read my post below. Attached is a photo of Singapore in media some days ago. It seems their pollution level had gone to hazardous levels. Not because the well managed and clean city-state did any mistake, but because of Indonesia burning their forests. The fires of Indonesia themselves seem a little suspicious. They didn't happen naturally but were lit widely by humans - specifically companies. Right at a time when the wind will turn towards Singapore. So the Singapore govt is now taking some extreme steps like going after these culprit companies even if they are based outside Singapore. Good work by their govt. But here's what Indians need to understand. Delhi or Mumbai pollution getting worse at this time of the year is not because of automobile, not because of road dust, not because of construction activity as they are all always blamed. They do contribute their bit, but never as much as farm fires. Just like Singapore facing Indonesian farm and forest fires, Indian cities face farm fires lit by our Anna Datas in many provinces. The govt and local authorities are afraid of them. They have already been encouraged to use machines and compactors but they wont. If authorities go to tell them to use it, they may get violent and force the authorities to burn the farms themselves. Now what I feel is going on is some kind of deliberate burning at the right time, using wind direction, to cause pollution in Delhi and Mumbai. Just like Singapore is being hit with pollution from Indonesia by some companies. So people can protest all they want against Delhi and Mumbai govt in the coming months. They can imagine if they do a "regime change" this pollution issue will go away. But this pollution isn't going away until farm burning stops.
- Oct 17, 20268.4x their median
તમારી સુરક્ષા માટે ગુજરાત પોલીસ હંમેશા તૈયાર છે. Dial 112. #GujaratPolice https://t.co/cxOP7N97RC
- Aug 21, 20268.1x their median
Today, we’re launching Meteoric (YC S26). Our drones clear clouds over solar farms to increase their annual output by 10-30% without using any chemicals. Ultimate target: weaken severe storms and hurricanes. https://t.co/Vt1ZGbMith https://t.co/ISjbavdeDD
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 870 interactions against 924K followers, an engagement rate of 0.094%. Measured over 26 original posts, its engagement rate beats 69% of 21,624 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 127K times each, and 0.682% of those impressions turn into an interaction. That is about 13.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 06:00 UTC, and Wednesday is the busiest day of the week. Of the 26 posts sampled, 92% carry an image or video and 12% link out. The account's strongest tracked post pulled 36K interactions, about 42x its own typical post. Recurring topics include #dpupdates, #gujaratpolice.
- What is Vijay Shekhar Sharma's engagement rate on X?
- Vijay Shekhar Sharma (@vijayshekhar) has an engagement rate of 0.094%, based on the median interactions across 26 original posts from the last 30 days against 924,372 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.094%, Vijay Shekhar Sharma sits above the 25th percentile of the 218,065 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 @vijayshekhar have real engagement?
- Its engagement rate beats 69% of the tracked X accounts closest to it in follower count (21,624 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 @vijayshekhar post?
- Most posts go out around 06:00 UTC, and Wednesday is its busiest day, at roughly 2.5 posts per day across the measured window.