Twitter Trends Scraper | Real-time X Trending Topics by Country

Scrape real-time X (Twitter) trending topics by country, city, or worldwide with optional historical windows, multi-location batch input, and sparkline history. This Apify Actor accepts location targets and time-window settings, then returns one dataset record per trend per location per window. Each record includes the trend name, rank, location, window label, source links, and optional history so you can review what was trending and how the rank moved over time. It runs over HTTP via getdaytrends.com, requires no login, and is ready for use through Apify MCP.

Best fit and connected workflows

This Actor fits workflows that need current or historical trend snapshots from X without building a browser scraper.

Use it when you want to:

• compare trends across several countries or cities in one run,
• pull a live Top 50 board for one location,
• review a past snapshot from 1h to 7d back,
• filter for hashtag-led trends,
• collapse repeated trend names across locations into one combined row,
• list supported locations as dataset rows for discovery workflows.

Because each row is tied to one location and one time window, the output works well as an input to dashboards, alerting logic, editorial planning, or AI agent pipelines that need structured trend data.

Focused standalone workflow

Twitter Trends Scraper | Real-time X Trending Topics by Country is designed as a focused standalone workflow.

Practical scenario

A social media manager starts with three locations: Worldwide, United States, and Japan. They choose the live window and keep the default history enabled. The dataset returns ranked trend rows with fields such as name, rank, location, windowLabel, searchUrl, and history. The manager sees that the same topic appears across multiple locations and decides to open the searchUrl for the top-ranked item in X search, then share the trend list with the content team for same-day post planning.

Input fields

Field	Type	Default	Description
locations	string[]	["worldwide"]	Locations to scrape. Accepts slugs, display names, full getdaytrends URLs, or WOEID integers.
window	string	now	Snapshot to fetch. Use now, 1h, 2h, 3h, 6h, 12h, 24h, 2d, 3d, 7d, or custom.
customDateTime	string	-	UTC timestamp used when window is custom.
maxTrendsPerLocation	integer	50	Maximum rows returned per location per window.
hashtagOnly	boolean	false	Return only trends that start with #.
deduplicateAcrossLocations	boolean	false	Collapse repeated trend names across locations into one row with locations[].
includeHistory	boolean	true	Attach compact sparkline rank history when available.
listAvailableLocations	boolean	false	Return the supported location catalog as dataset rows instead of trend rows.
proxyConfiguration	object	Apify residential preset	Proxy settings for HTTP requests.

Focused input example

{
  "locations": ["worldwide", "united-states", "japan"],
  "window": "now",
  "maxTrendsPerLocation": 20,
  "hashtagOnly": false,
  "deduplicateAcrossLocations": true,
  "includeHistory": true
}

Output fields

Field	Type	Description
recordType	string	Record type, set to trend for trend rows.
rank	integer	Position in the ranked list, where 1 is the top trend.
name	string	Trend name as displayed on X trends.
hashtag	boolean	Whether the trend starts with #.
url	string	getdaytrends detail page URL.
searchUrl	string	Direct X search URL for the trend.
volume	integer or null	Approximate tweet volume when derivable.
volumeLabel	string or null	Human-friendly volume label when available.
category	string or null	Category label when the source provides one.
promoted	boolean	Whether the trend is marked as promoted.
location	string	Human-friendly location label.
locationSlug	string	Source slug used to build the URL.
woeid	integer or null	WOEID for the location when known.
windowLabel	string	Snapshot label such as Now, 1h, or 7d.
windowHoursBack	integer	Hours back from now, where 0 means live.
windowTimestamp	string or null	ISO timestamp for the snapshot when available.
history	array	Compact rank-history samples parsed from the sparkline.
source	string	Source used for the record, such as getdaytrends.
scrapedAt	string	ISO timestamp when the row was scraped.

Illustrative output record

{
  "recordType": "trend",
  "rank": 1,
  "name": "Example Trend",
  "hashtag": false,
  "url": "https://getdaytrends.com/worldwide/trend/Example-Trend/",
  "searchUrl": "https://x.com/search?q=Example%20Trend",
  "volume": null,
  "volumeLabel": null,
  "category": null,
  "promoted": false,
  "location": "Worldwide",
  "locationSlug": "worldwide",
  "woeid": 1,
  "windowLabel": "Now",
  "windowHoursBack": 0,
  "windowTimestamp": null,
  "history": [
    {
      "t": "2026-08-02T15:00:00.000Z",
      "rank": 1
    }
  ],
  "source": "getdaytrends",
  "scrapedAt": "2026-08-02T16:12:34.000Z"
}

How it works

The Actor builds one getdaytrends URL per requested location and time window. It fetches server-rendered HTML over HTTP, then extracts trend rank, name, source URLs, and sparkline history from the page. The dataset stores one trend row per location per window, and the run summary is written to the key-value store for downstream review. The live contract also defines OUTPUT and RUN_SUMMARY records for run-evidence workflows.

Pricing

Twitter Trends Scraper | Real-time X Trending Topics by Country uses Pay per event billing plus Apify platform usage.

• One event is charged when the Actor starts.
• One event is charged for each trend row written to the dataset.

For a simple example in words: if you request one location and receive fifty trend rows, the run is billed for one start event and fifty trend events, plus platform usage. For multi-location runs, the billed trend count scales with the number of returned rows across all selected locations and windows.

To review the current pricing details, open the live Pricing tab in the Apify Console. That tab shows the active event billing and platform usage information for this Actor.

Use with AI agents (MCP)

This Actor is available through Apify MCP as a tool for retrieving structured X trend snapshots.

Tool description:

Get structured X trending topics by location and time window. Returns ranked trend rows with optional history, location metadata, source links, and search URLs. Suitable for social monitoring, news tracking, editorial planning, and location-by-location comparison.

Actor identity: khadinakbar/twitter-trends-scraper

"Fetch the live trend board for Worldwide, United States, and Japan. Return up to 20 rows per location, keep history on, and deduplicate repeated names across locations so I can compare the results quickly."

How to interpret the output:

• rank tells you the order within each location and window.
• location, locationSlug, and woeid identify where the trend was captured.
• windowLabel and windowTimestamp tell you which snapshot you received.
• searchUrl is useful for opening the topic directly in X search.
• history[] provides compact rank samples when sparkline history is available.

Provenance and scope:

The data comes from getdaytrends.com, which mirrors public X trend boards. The Actor works over HTTP and is MCP-ready, so agents can call it as a structured data tool without a browser session.

Pagination and cost guidance:

Each row returned is billed as a trend event. For planning, estimate cost from the number of locations multiplied by maxTrendsPerLocation, then adjust for deduplication or smaller row caps when you only need a subset. When listAvailableLocations is enabled, the Actor returns the supported location catalog instead of trend rows.

Apify API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const run = await client.actor('khadinakbar/twitter-trends-scraper').call({
  locations: ['worldwide', 'united-states'],
  window: 'now',
  maxTrendsPerLocation: 10,
  includeHistory: false,
});

const datasetId = run.defaultDatasetId;
const { items } = await client.dataset(datasetId).listItems();

console.log('Dataset items:', items);

Best results and outcome guidance

Use the smallest location set that matches the workflow. If you only need the current board, keep window on now. If your workflow depends on trend movement, enable includeHistory. If you are comparing markets, leave deduplication off to preserve one row per location. If you are gathering a campaign-ready hashtag list, use hashtagOnly together with a lower row cap.

Design note

I found that the dataset contract is centered on one trend record per location per time window, with rank, name, location, source, and scrapedAt required on every row. That shape makes the output straightforward to join into downstream workflows.

FAQ

Can I request several markets in one run?

Yes. The locations field accepts multiple location values, so one run can return trend rows for several countries or cities.

Can I get a past trend snapshot?

Yes. Use window values such as 1h, 6h, 24h, 2d, 3d, or 7d, or set window to custom and provide customDateTime.

How do I compare the same trend across locations?

Set deduplicateAcrossLocations to true. Matching trend names are collapsed into one row with a locations[] array.

How do I return only hashtag trends?

Set hashtagOnly to true. The dataset then includes only trends that start with #.

Can I list supported locations before scraping trends?

Yes. Set listAvailableLocations to true and the Actor returns the supported location catalog as dataset rows.

Responsible use

Use this Actor for public trend analysis, monitoring, editorial workflows, and similar lawful purposes. Review your own obligations under X terms, getdaytrends terms, and applicable laws before building production workflows on top of the output.