X Trends Scraper by Country

Pull the live X (Twitter) trending list for any country or city X ranks. Rank, topic name, the search URL, whether it is a hashtag, whether it is promoted, and X's own timestamps for when the list was built.

467 locations available: 62 countries, 402 cities, plus worldwide. Up to 50 trends each.

No login. No cookies. No browser. No Twitter account.

What makes this one worth using

Same price on every Apify plan. $0.40 per 1,000 trends on the free plan and on every paid plan. No free-tier multiplier, no reduced result cap for free users.

An empty location costs nothing. If X publishes no trends for a place at the moment you ask, you get a FAILURES entry saying so — not a padded row and not a charge.

A location X does not rank is an error, not an invoice. Ask for "Atlantis" and the run tells you X ranks 62 countries and around 400 cities, and that yours is not one of them. It does not return an empty object and bill you for it.

tweetVolume is reported as null, because that is what X returns. Verified across Worldwide, the United States, Brazil, Mexico, Peru and India on 2026-08-22: X returns null for volume on every trend in every location. This actor passes that through untouched. It does not estimate, interpolate, or substitute a plausible-looking number. If you see a trending-topic scraper showing you tweet volumes, ask where the number came from.

Input

{
  "countries": ["worldwide", "United States", "PE", "Lima", "23424768"],
  "maxItemsPerTarget": 50
}

Locations can be given in whatever form you have them:

You pass	It resolves to
"worldwide", "world", "global"	The global list
"Peru"	The country
"PE"	The country, by ISO code
"Lima"	The city, when includeCities is on
"23424919"	Directly by WOEID
"all"	Every one of the 62 countries
"all cities"	Every one of the 402 cities

Field	Type	Default	What it does
countries	array	["worldwide"]	Locations. Aliases: country, places, place, locations, location, woeids, woeid.
maxItemsPerTarget	integer	50	Per-location ceiling. X publishes at most 50. Aliases: maxTrendsPerPlace, perTargetLimit.
maxItems	integer	none	Ceiling across the whole run. Aliases: maxResults, limit, maxTrends.
includeCities	boolean	false	Let ambiguous names resolve to cities. Off by default, so "Mexico" gives you the country.

On date filters

A trending list is a live snapshot. There is no per-trend timestamp to filter on, so a date filter is rejected with an explicit error rather than accepted and ignored:

X Trends Scraper by Country cannot filter by date on this data (startDate was supplied). X does not expose a usable timestamp for this surface, so honouring the filter is impossible and ignoring it would hand you rows outside your range. This actor has no date filter.

What you get instead is honest freshness metadata on every row — see below. To build a time series, schedule the actor and let each run be one snapshot.

Output

One row per trend.

Field	Notes
rank	1 to 50, in the order X returned them.
name	The trend as displayed, e.g. #SmackDown or Nick Chubb.
isHashtag	Whether the name starts with #.
query	The decoded search query behind the trend.
searchUrl	A working https://x.com/search?q=... link.
isPromoted	Whether it is a paid placement rather than an organic trend.
tweetVolume	Always null. X stopped publishing it. Reported honestly, never estimated.
placeName, placeType, woeid	The location, its type (Country, Town, Supername), and its WOEID.
countryName, countryCode	Filled for cities too, so city rows still group by country.
trendsAsOf	X's as_of timestamp for the response.
listGeneratedAt	X's created_at — when it actually built the list.
scrapedAt	When this actor fetched it.

The freshness detail nobody mentions

trendsAsOf and listGeneratedAt are not the same thing, and the gap is often hours. Measured on 2026-08-22: the Worldwide list reported as_of at 04:02 UTC but created_at at 00:19 UTC the previous day — a gap of nearly 28 hours. The United States list showed 04:02 against 09:52 the day before.

listGeneratedAt is when X actually computed the ranking. If you are timestamping a trend for analysis, that is usually the field you want, and this actor passes both through so you can decide. The freshness dataset view puts them side by side with scrapedAt.

How it works

Two endpoints, both of which x.com serves to logged-out clients:

1. GET /1.1/trends/available.json — X's full catalogue of ranked locations, fetched fresh at the start of every run rather than hardcoded, so the actor tracks locations X adds or drops.
2. GET /1.1/trends/place.json?id=<woeid> — the current list for one location.

Authentication is a guest token from POST /1.1/guest/activate.json: free, tied to no account, and refreshed automatically inside the run whenever X rotates or rejects it.

No browser, no proxy required, 512 MB of memory. Fetching all 62 countries takes under a minute.

Errors go where you can act on them

Nothing that failed is written into the dataset. It goes into the FAILURES key-value record:

{
  "actor": "X Trends Scraper by Country",
  "targetsRequested": 3,
  "resultsDelivered": 15,
  "resultsCharged": 15,
  "failureCount": 1,
  "failures": [
    {
      "target": "Atlantis",
      "error": "X does not publish a trend list for \"Atlantis\". It ranks trends for 62 countries and around 400 cities only."
    }
  ],
  "notes": [
    "tweetVolume is null on every row because X stops publishing it to logged-out clients. It is reported as null rather than estimated."
  ]
}

A run that delivers nothing is marked FAILED, not quietly succeeded over an empty dataset. You are charged nothing either way.

Pricing

$0.40 per 1,000 trends. Pay per result. No subscription. Same price on every Apify plan.

What you fetch	Trends	Cost
Worldwide only	50	$0.02
One country	up to 50	$0.02
Ten countries	up to 500	$0.20
Every country ("all")	up to 3,100	$1.24
Every country, hourly for a month	~2.2M	~$900
Every country, every 6 hours for a month	~372,000	~$149

Locations X does not rank, and locations with no trends right now, cost $0.00.

Typical uses

• Multi-market social listening. Fetch all 62 countries in one run and see which topics cross borders and which stay local. A single run costs $1.24.
• A trend time series. Schedule the actor hourly against your markets and append to the same dataset. listGeneratedAt gives you an honest x-axis. This is the closest thing to a historical trends archive you can build without paying enterprise rates, and building it early is the whole point.
• Content and newsroom timing. Know what is trending in your target market before you publish, in the market's own language.
• Ad-buying context. isPromoted separates paid placements from organic ones, which tells you who is buying attention in a market right now.
• Localisation research. Compare the same brand or event across Spain, Mexico, Argentina and Peru to see how framing shifts.
• Hashtag discovery. Filter isHashtag and take the live hashtag set for a market straight from X's own ranking.

Limits worth knowing before you start

• 62 countries, not 195. X ranks trends only for the locations it chooses to. The list is fetched live at the start of each run, so it is always current, and anything outside it is reported as a clear failure rather than billed.
• tweetVolume is always null. Covered above. This is X's behaviour, not a gap in the actor.
• The lists move on X's schedule, not yours. listGeneratedAt can lag trendsAsOf by many hours. Polling faster than X regenerates gets you duplicate snapshots — which you would still be charged for, so use listGeneratedAt to deduplicate.
• No historical data. X publishes the current list only. History is something you accumulate by scheduling this actor, not something anyone can retrieve retroactively.
• No keyword search. This actor reports what X ranks. It does not search X, because X blocks the search timeline for guests entirely.

Verified

Every endpoint, field, location count and null-volume claim in this README was tested live against X on 2026-08-22 from a datacenter IP with no cookies and no account. The 467 locations, the 62 countries and the as_of versus created_at gap are measurements from that day.

Related actors

• Tweet Scraper by URL or ID — individual tweets with full metrics, $0.20/1k.
• X Profile Scraper - No Login — bulk handle-to-profile lookup, $0.25/1k.
• X Profile Posts Scraper - No Cookies — an account's timeline with a real per-account cap, $0.30/1k.
• Tweet Replies Scraper - No Login — publicly visible replies, $0.30/1k.

Same rules across all of them: one price on every plan, and nothing charged for nothing.