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Google Students engagement report

@googlestudents - 443K followers on X

Measured over 12 original posts from a 30-day window, last computed on October 30, 2026.

Engagement

Middle of its size range
Per follower
0.005%
of 443K followers
Per impression
0.82%
2.7K views on a typical post
Reach
0.62%
of its followers see a post
Typical post
22
interactions (median)
Saved
0.146%
4 bookmarks on a typical post
Posting rate
0.57/day
active 40% of days
Peak time
14:00 UTC
Thursday

A typical post picks up 22 interactions against 443K followers, an engagement rate of 0.005%. Measured over 12 original posts, its engagement rate beats 25% 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 2.7K times each, and 0.82% of those impressions turn into an interaction. That is about 0.62% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.57 post a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 12 posts sampled, 100% carry an image or video, 25% are part of a thread and 75% link out. The account's strongest tracked post pulled 1.9K interactions, about 86x its own typical post.

Measured over 12 original posts from a 30-day window, last computed on October 30, 2026.

Compared with accounts its own size

Google Students's engagement rate beats 25% 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 41% 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 0.005%, Google Students sits above the 10th percentile of the 217,745 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.

p100.004%
p250.025%
p50 (median)0.149%
p750.704%
p902.63%
p9982.5%
Engagement rate as a share of followers, across the 217,745 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 21,722 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 percentile0.149%
75th percentile0.704%
90th percentile2.63%
99th percentile82.5%

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 14:00 UTC, and Thursday 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: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 14:00 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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Thursday
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 link75% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 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.
  • 75% 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 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

  • Aug 31, 202686x their median

    Applications for our 2027 Software Engineering Internships are now live on Google's Careers site! Before you apply, head to our new Student Hub for resume tips, interview prep resources, and everything you need to know about the internship experience ➡️ https://t.co/skMtp51Mpk https://t.co/E1AHRQxSzt

    1.7K1893110110K viewsView on X
  • Sep 14, 202617x their median

    It's back-to-school season! As the fall semester kicks off, we're excited to share that Google internships for 2027 — including our Software Engineer roles — are beginning to open. Explore our opportunities for students and apply today: https://t.co/9ie4PfZ015 https://t.co/dCc1VBQJbn

    331277124K viewsView on X
  • Sep 4, 202615x their median

    Google’s 2027 SWE internship applications are now open! Before you apply, hear directly from the 2026 intern class on what helped them succeed. Watch their advice and apply today ➡️ https://t.co/djmgZTsiBa https://t.co/sO8zWXAul7

    303295015K viewsView on X
  • Sep 8, 20269.9x their median

    Mara liked her first Google internship so much, she came back for another. This time, she's making fitness feel more personal. As a Software Engineering Intern in Google Health, she’s building the backend infrastructure that helps make health data easier to process. https://t.co/eoVhVDzyXt

    2055629.7K viewsView on X
  • Sep 9, 20266.7x their median

    Ben — a Technical Recruiter at Google — shared his top 5 tips for interested applicants. Listen to Ben's advice, then explore our open career opportunities ➡️ https://t.co/kPIDyioMHT https://t.co/jHzPfTajrC

    1387309.5K viewsView on X
  • Jul 23, 20266.0x their median

    The fastest way to understand how massive AI models work isn't just studying them — it's building the frameworks that test them. Google DeepMind Software Engineering intern Jonathan breaks down how he uses benchmarks and evals to help Gemini run "hillclimbing" (continuous optimization).

    108165339K viewsView on X
  • Oct 20, 20264.8x their median

    Meet Uma, a software engineer on Google’s Borglet team. Her team builds the core technology behind Google’s own services and the Google Compute Engine customers who rely on them. Uma was “drawn to Google by the sheer scale of impact possible here.” Soon after Noogler orientation, she found that “collaborating with brilliant colleagues across the office left [her] constantly inspired and motivated.”

    944806.9K viewsView on X
  • Sep 17, 20264.7x their median

    Have questions about landing a role at Google? Join our live Recruiter Ask Me Anything TODAY, September 17, at 12:00 PM PT! Google Recruiters are ready to answer all your questions about life at Google, resume tips, and our latest student opportunities. Don't miss this chance to get insider advice directly from the team ➡️ https://t.co/aBv8VdPimF

    9410009.9K viewsView on X
  • Sep 23, 20264.4x their median

    Devina, a Software Engineering intern at Google's Zurich office, shares her best advice for students preparing to apply for next summer's internships. Read her tips, then explore our open opportunities for students and early career professionals ➡️ https://t.co/9ie4PfZ015 https://t.co/gUNQz00KXQ

    868307.8K viewsView on X
  • Sep 16, 20264.3x their median

    How do we build safer AI agents? Meet Alaia, a PhD student and Google Student Researcher working to tackle this exact challenge. Learn more about her work, the challenges she’s navigated along the way, and the future implications of her research — then explore our open career opportunities for students ➡️ https://t.co/8dOBnVFwJT

    858107.4K 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.

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Reading these numbers

A typical post picks up 22 interactions against 443K followers, an engagement rate of 0.005%. Measured over 12 original posts, its engagement rate beats 25% 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 2.7K times each, and 0.82% of those impressions turn into an interaction. That is about 0.62% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.57 post a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 12 posts sampled, 100% carry an image or video, 25% are part of a thread and 75% link out. The account's strongest tracked post pulled 1.9K interactions, about 86x its own typical post.

What is Google Students's engagement rate on X?
Google Students (@googlestudents) has an engagement rate of 0.005%, based on the median interactions across 12 original posts from the last 30 days against 443,044 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Google Students sits above the 10th percentile of the 217,745 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 @googlestudents have real engagement?
Its engagement rate beats 25% 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 @googlestudents post?
Most posts go out around 14:00 UTC, and Thursday is its busiest day, at roughly 0.57 posts per day across the measured window.

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