Back to @zhang_heqing's profile

Zhang Heqing engagement report

@zhang_heqing - 446K followers on X

Measured over 26 original posts from a 30-day window, last computed on August 29, 2026.

Engagement

Bottom quarter for its size
Per follower
0.005%
of 446K followers
Per impression
0.802%
2.6K views on a typical post
Reach
0.57%
of its followers see a post
Typical post
20
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
2.47/day
active 13% of days
Peak time
11:00 UTC
Saturday

A typical post picks up 20 interactions against 446K followers, an engagement rate of 0.005%. Measured over 26 original posts, its engagement rate beats 22% of 3,758 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.6K times each, and 0.802% of those impressions turn into an interaction. That is about 0.573% 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, though only 13% of days saw any activity at all. Most posts go out around 11:00 UTC, and Saturday is the busiest day of the week. Of the 26 posts sampled, 100% carry an image or video and 12% link out. The account's strongest tracked post pulled 14K interactions, about 718x its own typical post. Recurring topics include #china, #chinamustanswer, #debatewitharnab.

Measured over 26 original posts from a 30-day window, last computed on August 29, 2026. Recurring tags: #china, #chinamustanswer, #debatewitharnab.

Compared with accounts its own size

Zhang Heqing's engagement rate beats 22% of the tracked X accounts closest to it in follower count (3,758 accounts, accounts of similar size (decile 7 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 44% 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%, Zhang Heqing sits above the 10th percentile of the 36,521 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.

p100.002%
p250.012%
p50 (median)0.08%
p750.434%
p902.10%
p99160.7%
Engagement rate as a share of followers, across the 36,521 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,166 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 percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.434%
90th percentile2.10%
99th percentile160.7%

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 11:00 UTC, and Saturday 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: 11:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 11:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%50K
01:00 UTC-2%51K
02:00 UTC-3%50K
03:00 UTC-4%53K
04:00 UTC-6%43K
05:00 UTC-4%42K
06:00 UTC-4%48K
07:00 UTC-5%52K
08:00 UTC-4%60K
09:00 UTC-3%69K
10:00 UTC-2%72K
11:00 UTC-3%78K
12:00 UTC-2%86K
13:00 UTC-2%94K
14:00 UTC-4%97K
15:00 UTC-2%100K
16:00 UTC-3%97K
17:00 UTC-2%90K
18:00 UTC-1%84K
19:00 UTC-2%79K
20:00 UTC-1%74K
21:00 UTC-1%66K
22:00 UTC-2%57K
23:00 UTC-2%51K
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: Saturday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Saturday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%230K
Monday0%286K
Tuesday-2%276K
Wednesday-1%251K
Thursday-1%244K
Friday-3%252K
Saturday+3%227K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Aug 29, 2026718x their median

    "Is anybody here? Is anybody here?" Chinese first rescue team is searching the core disaster area of the Gyirong Port. The whole area is buried under the mud. Rescuers knock and call out, trying to find anyone who may still be alive. Be careful and stay safe🙏 https://t.co/WkIhJIY0zq

    13K1.3K225941.0M viewsView on X
  • Aug 29, 2026117x their median

    While the USA spends trillions on wars, China spends trillions on building a nation worthy of its people's dream. The Chinese Dream is where everyone becomes more prosperous together. https://t.co/l2sLN0ub62

    1.7K476994877K viewsView on X
  • Aug 28, 202651x their median

    #ChinaMustAnswer | “You are using Tibet like a laboratory; why does one region have 10 dams?”: Major Samar Pal Toor (@MajorSammerToor)(@samartoor3086), Defence Expert. Watch #DebateWithArnab now, on-air, and online. Tune in and fire in your comments: https://t.co/tZgOcXxRbT #NepalFloods #BharatWithNepal #NepalDisaster #ChinaNepalBorder #ChinaMadeDisaster #HimalayanDisaster #ChinaWarning #TibetFloods #BarrierLake #GlacierCollapse #NepalFloodUpdate #NepalChinaNews #ArnabGoswami #RepublicWorld

    8041563821318K viewsView on X
  • Aug 29, 202646x their median

    A mudslide that flowed upstream — then came back. This on-site report from CCTV correspondent Xu Zhuoyang was filmed about 1 km from the Gyirong Port, on the China-Nepal border in Xizang. Look at the roadside stakes: they've all fallen toward the direction the mud came from — the opposite of what you'd expect. Local firefighters explained why: the mudslide first surged upstream from the port side, then, losing momentum at a certain height, flowed back down. The stakes were scoured twice. One small detail on the ground, and the whole force of the disaster becomes visible.

    7681171414203K viewsView on X
  • Aug 29, 202626x their median

    President Xi Jinping called on China and Kyrgyzstan to work together to create a new chapter of high-quality development in bilateral relations in an article published in Slovo Kyrgyzstana and Kabar National News Agency. Full text: English: Jointly Opening up New Prospects for the High-Quality Development of China-Kyrgyzstan Relations https://t.co/bk2OuB6T0l Russian: КИТАЙ И КЫРГЫЗСТАН: ВМЕСТЕ К НОВЫМ ГОРИЗОНТАМ ВЫСОКОКАЧЕСТВЕННОГО РАЗВИТИЯ ДВУСТОРОННИХ ОТНОШЕНИЙ https://t.co/3yBO6zBzXY

    3996449692K viewsView on X
  • Aug 29, 202619x their median

    新华社发布3分钟动画,直观解析吉隆泥石流灾害全过程 https://t.co/ClOtFp3oc0

    3106211548K viewsView on X
  • Aug 28, 202619x their median

    Anyone accusing China of causing this disaster, or criticizing the rescue operations for being slow or information disclosure for being untimely, is either harboring despicable, malicious intent or is simply ignorant of the facts. Analyses by numerous experts and scholars—along with satellite imagery, on-site photos, and videos (including those from the Nepalese side)—confirm that the ice avalanche originated on a high mountain within Nepalese territory, upstream and to the northeast of the Chinese border crossing. The event was not caused by a single factor but resulted from the interplay of long-term influences such as climate change, glacial melting, earthquakes, and recent rainfall. Furthermore, the terrain at the Chinese border crossing and the area immediately to its north is narrow and situated right next to the river channel. When the debris flow and floodwaters struck the crossing's structures and the surrounding rock faces, the flow was split: part of it surged northward—upstream and against the river's current—slamming into the Chinese crossing's parking lot, buildings, and roads (completely burying and destroying the roads within a span of just 1.5 to 2 kilometers), while the rest continued southward into the open terrain of Nepal, causing widespread devastation for dozens of kilometers downstream. Consequently, rescue operations on the Chinese side are far more difficult than on the Nepalese side. There are simply no passable roads; heavy machinery and large numbers of rescue personnel are stalled in towns and on roads about 20 kilometers to the north, unable to advance. Road repair efforts are hampered by ongoing cliff collapses, thick mud, and turbulent waters. Meanwhile, a new barrier lake containing millions of cubic meters of water has formed upstream in the valley and is showing signs of breaching; there is also fresh ice and snow instability, compounded by forecasts of rain in the coming days. Video footage shows that accessing the hardest-hit areas of the crossing is still only possible by traversing mountain ridges or via airdrops, though even these methods are constrained by the terrain. Local communications and lighting have been restored; let us pray for a smooth operation—with less blame and hostility, and more prayers. China is a key trading partner for Nepal, and the entire border region is characterized by similar high-mountain gorges. No one wishes for such disasters, nor can they be predicted in advance. Hopefully, more effort and resources will be invested in the future toward the monitoring, early warning, and study of such hazards.

    2876428531K viewsView on X
  • Aug 27, 20269.5x their median

    The kindergarten and school at a relocation area for Darya Boyi Town in Yutian County, northwest China's Xinjiang Uygur Autonomous Region. A resettlement plan moved poor local residents to where better housing, drinking water facilities and roads are built. The Yutian County government, which administers the town, started to draft plans for resettlement in 2016. Today, locals enjoy new lives thanks to China's drive to end all extreme poverty in the country. People were volunarily moved to modern homes in better locations with new schools, a hospital and nearby access to markets, towns, and arable land. All homes have clean water, electricity, and 5G wifi.

    138341444.6K viewsView on X
  • Aug 29, 20268.9x their median

    “你怎么不去南京谢罪呢?”日本驻以大使翻大车!北京时间8月26日下午,日本驻以色列大使馆发布的一则网帖,引起了中外网民的群嘲。该网帖显示,日本驻以色列大使新居雄介,为了搞好与以色列的关系,不仅在欧洲访问时专程去了二战时纳粹德国在波兰修建的奥斯维辛集中营,还宣称自己“有义务”让世界铭记被纳粹屠杀的犹太人。

    150181106.6K viewsView on X
  • Aug 29, 20262.3x their median

    Fear is human instinct. But in last seconds before the mudslide hit, this Chinese border police officer was still evacuating others. He’s a true hero🙏🏻 https://t.co/P5vxLx3fB1

    432015.0K 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

#china#chinamustanswer#debatewitharnab#mudslide#xizang

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.

Buy or sell X accounts - escrow-protected

PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.

Reading these numbers

A typical post picks up 20 interactions against 446K followers, an engagement rate of 0.005%. Measured over 26 original posts, its engagement rate beats 22% of 3,758 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.6K times each, and 0.802% of those impressions turn into an interaction. That is about 0.573% 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, though only 13% of days saw any activity at all. Most posts go out around 11:00 UTC, and Saturday is the busiest day of the week. Of the 26 posts sampled, 100% carry an image or video and 12% link out. The account's strongest tracked post pulled 14K interactions, about 718x its own typical post. Recurring topics include #china, #chinamustanswer, #debatewitharnab.

What is Zhang Heqing's engagement rate on X?
Zhang Heqing (@zhang_heqing) has an engagement rate of 0.005%, based on the median interactions across 26 original posts from the last 30 days against 446,018 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Zhang Heqing sits above the 10th percentile of the 36,521 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 @zhang_heqing have real engagement?
Its engagement rate beats 22% of the tracked X accounts closest to it in follower count (3,758 accounts), which puts it in the bottom quarter for its size 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 @zhang_heqing post?
Most posts go out around 11:00 UTC, and Saturday is its busiest day, at roughly 2.47 posts per day across the measured window.

Keep going