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HPE Developer Community engagement report

@HPE_Developer - 163K followers on X

Measured over 6 original posts from a 30-day window, last computed on October 24, 2026.

Engagement

Per follower
0.003%
of 163K followers
Per impression
1.38%
327 views on a typical post
Reach
0.2%
of its followers see a post
Typical post
4
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
0.2/day
active 20% of days
Peak time
13:00 UTC
Monday

Early reading. We have captured 6 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 4 interactions against 163K followers, an engagement rate of 0.003%. Posts are seen about 327 times each, and 1.38% of those impressions turn into an interaction. That is about 0.201% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 6 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 10 interactions, about 2.5x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 6 original posts from a 30-day window, last computed on October 24, 2026. Recurring tag: #hpedev.

Where this sits in the catalog

At 0.003%, HPE Developer Community sits below the 10th percentile of the 212,349 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.

p100.004%
p250.025%
p50 (median)0.146%
p750.696%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 212,349 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,452 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.025%
50th percentile0.146%
75th percentile0.696%
90th percentile2.61%
99th percentile83.1%

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 13:00 UTC, and Monday 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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 13:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 13:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video100% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 100% 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.
  • 100% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 267 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

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

  • Sep 30, 20262.5x their median

    Chapel 2.10 is here! This release brings complete and productive union types, stack traces for thrown errors, and expanded public testing through GitHub Actions. Explore the highlights and see what’s new. #HPEDEV https://t.co/LjcRYfznwo https://t.co/8PolisNi3u

    7300359 viewsView on X
  • Jul 8, 20262.3x their median

    New in Chapel 2.9: support for dynamic libraries, better code editing via CLS, and advanced union types. Explore what's new in this summer release! #HighPerformanceComputing #Chapel #HPEDEV https://t.co/Awxfh7aylt https://t.co/ryXEqfB9Pr

    6300313 viewsView on X
  • Sep 28, 20261.5x their median

    What happens when an AI coding-agent harness moves from TypeScript to Go? PiG is the result: a native, portable runtime with multi-language extension support, named agent compositions, and a growing focus on parity with Pi. Read the story. https://t.co/1CsqVGCWCu #HPEDEV https://t.co/MpPpr1Y6S7

    3210360 viewsView on X
  • Sep 25, 20261.5x their median

    Discover how purpose-built compute is transforming edge AI—delivering secure, resilient, and mission-specific infrastructure that turns data into actionable insights right where decisions happen. Read more! #HPEDEV https://t.co/pU1T9hiclB https://t.co/XYEPMLt9kB

    4200295 viewsView on X
  • Aug 12, 20261.5x their median

    Mark your calendar for the upcoming #HPEDEV meetup, where our experts will go through the latest on HPE Morpheus, the HPE Terraform provider integration, and the new Terraform provider migration tool, with live demonstrations and open Q&A. https://t.co/o8mz0lvMET https://t.co/pBlmyLzNac

    3300422 viewsView on X
  • Sep 21, 2026

    Join our next HPE Developer Community 's Meetup to discover how HPE CloudOps Software – Advanced streamlines private cloud ops with integrated provisioning and observability. Automate deployment, enhance visibility, and accelerate troubleshooting. Join us! #HPEDEV https://t.co/4Y9AkGgHEu

    3200390 viewsView on X
  • Aug 31, 2026

    Curious how Arkouda handles a trillion rows of data? Our new blog explores its single-pass, parallelized approach to massive data challenges — surpassing Dask in speed and efficiency. Check it out! #HPEDEV https://t.co/ydTOPQUyPt https://t.co/v7WAWwxyqp

    3200645 viewsView on X
  • Aug 10, 2026

    Understanding AI token consumption is key to controlling costs and maximizing value. As AI becomes more agentic and complex, Tokenomics will be your new strategic language. See how. #HPEDEV https://t.co/AB5fHyc1PR https://t.co/3LQ5we2yeG

    4100354 viewsView on X
  • Jul 21, 2026

    Build your first AI agent on HPE Private Cloud AI with our easy-to-follow tutorial. No coding required: just deploy models, connect data, and go! #HPEDEV https://t.co/LYmzW0hBRg https://t.co/j5eJKPlpoh

    4100262 viewsView on X
  • Jul 6, 2026

    Part 4 of our #HPEDEV blog series on HPE OpsRamp observability covers the complete metric ingestion path - from Redfish hardware data through the OTel Python SDK, showing the precise coordination required across the 3 layers. https://t.co/SZ6vYTBESb https://t.co/JKEU0qRXLa

    3200257 viewsView on X

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

#hpedev

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 4 interactions against 163K followers, an engagement rate of 0.003%. Posts are seen about 327 times each, and 1.38% of those impressions turn into an interaction. That is about 0.201% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 6 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 10 interactions, about 2.5x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is HPE Developer Community's engagement rate on X?
HPE Developer Community (@HPE_Developer) has an engagement rate of 0.003%, based on the median interactions across 6 original posts from the last 30 days against 163,027 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.003%, HPE Developer Community sits below the 10th percentile of the 212,349 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 @HPE_Developer have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @HPE_Developer post?
Most posts go out around 13:00 UTC, and Monday is its busiest day, at roughly 0.2 posts per day across the measured window.

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