Trends Scraper

Work with preset X trend feeds from selected Explore tabs. This Actor can list preset trend timelines, fetch tweets for one concrete trend topic, and fetch relevant users for that trend.

About SIMO IT

SIMO IT builds practical social data products that support fast insight loops for marketing, PR, and growth teams.

Features

• collect posts from selected preset trend timelines
• follow preset categories like trending, news, sport, and entertainment
• preset categories map to X Explore tab feeds such as:
  • news: https://x.com/explore/tabs/news
  • sport: https://x.com/explore/tabs/sports
  • entertainment: https://x.com/explore/tabs/entertainment
• fetch tweets for one concrete trend topic using numeric trendId
• collect TrendRelevantUsers for one concrete trend topic by numeric trend rest_id
• monitor topic momentum and context
• paginate for deeper trend analysis

Use cases

• trendwatching and social listening
• real-time content planning
• spotting opportunities for rapid PR and marketing reactions

Output

Preset trend-feed content that can be used immediately in analysis, planning, and decision workflows.

Note: backend endpoint returns an envelope: { data: [...], page, limit, has_next }. This Actor pushes only records from data[] to the dataset.

How to use

1. Start with What do you want to fetch?.
2. For Discover trends, choose one preset category: trending, news, sport, or entertainment.
3. For tweets or relevant users, leave category empty and put the numeric value into trendId.
4. You can get that numeric id from a returned deep link such as twitter://trending/2025383938727051697.
5. Do not use the top-level trend item id like trend-Southampton Stun Arsenal 2-1 to Reach FA Cup Semis. Use the numeric value from trend_url.url or the helper field trend_id.
6. For tweet runs, choose Tweet feed: Latest or Top.
7. In most cases you do not need to touch Data mode in the Advanced section.
8. Configure pagination and caps as needed.

Important:

• this Actor works on preset trend categories, not the newer global-trending country/category feed
• if you want the fuller country/category-based trends product, use https://apify.com/simoit/x-twitter-trends-scrapper
• category is only for trends discovery
• trendId is required for tweets and relevant users
• if both are filled, the Actor prioritizes trendId
• invalid user input is reported as a successful run with a clear USER_ERROR_REPORT in the default key-value store instead of a generic crash
• dataset shape stays unchanged for existing clients; error details are written to key-value store and status message, not pushed as dataset records
• each run stores a RUN_REPORT key in the default key-value store with counts, warnings, and structured debug events

No technical setup is required from your side. Backend infrastructure is managed by SIMO IT.

Need a custom plan, custom limits, or a tailored data workflow? Contact contact@simoit.tech.

Related Actors

• Need country and category feeds from the newer global-trending surface? Use Global Trending Scraper.
• Need tweet search after discovering a trend topic? Use Tweet Scraper.
• Need to inspect what one account posted around a trend? Use Profile Scraper.
• Need account metadata or follower graphs for relevant users? Use User Scraper.

Input

• inputTargetType (string, recommended): Primary UI selector for the run intent.
  • discover_trends: list trends from one preset category
  • trend_tweets: fetch tweets for one concrete numeric trend id
  • relevant_users: fetch relevant users for one concrete numeric trend id
  • trend_tweets_and_users: fetch both datasets for one concrete numeric trend id
• trendId (string, conditionally required):
  • for trends: preset category (trending, news, sport, entertainment) or another backend-supported custom identifier
  • for tweets and relevant_users: numeric trend rest_id only, extracted from trend_url.url like twitter://trending/2040024758503477259
• trendName (string, optional): Optional label stored together with returned tweets/users.
• sort (string, optional, default: latest): Tweet timeline selection for one concrete trend.
  • latest: most recent tweets for the trend
  • top: top-ranked tweets for the trend
• category (string, optional): Preset trend category: trending, news, sport, or entertainment. These are preset Explore-style feeds, not the newer global-trending categories. Use only for discover_trends.
• trendUrl (string, optional): Single concrete X/Twitter trend URL.
• trendUrls (string, optional): Batch concrete trend URLs (comma-separated or new lines).
• startUrls (string, optional): Alias batch URL input (comma-separated or new lines).
• dataMode (string, optional, default: auto): Advanced override. Usually leave it untouched.
  • auto: choose the right flow automatically from the provided target
  • trends: list current trends/posts from preset categories or another backend-supported custom identifier
  • tweets: fetch tweets for one concrete numeric trend id
  • relevant_users: list relevant users for one concrete numeric trend id
  • both: run both flows explicitly
• page (integer, optional, default: 1): Starting page number.
• limit (integer, optional, default: 20, max: 100): Records per page.
• maxPages (integer, optional, default: 1): Maximum number of pages to fetch.
• maxItems (integer, optional): Hard cap for trend records.
• usersPage (integer, optional, default: 1): Starting page for trend relevant users.
• usersLimit (integer, optional, default: 20, max: 100): Relevant users per page.
• usersMaxPages (integer, optional, default: 1): Maximum pages for trend relevant users.
• usersMaxItems (integer, optional): Hard cap for trend relevant user records.

Filters and pagination

• trend target: trendId, category, trendUrl, trendUrls, startUrls
• mode switch: dataMode
• trend page controls: page, limit, maxPages, maxItems
• relevant users page controls: usersPage, usersLimit, usersMaxPages, usersMaxItems

Example input

Discover current sport trends:

{
  "inputTargetType": "discover_trends",
  "category": "sport",
  "limit": 10,
  "maxItems": 20
}

Fetch relevant users for one specific trend topic:

{
  "inputTargetType": "relevant_users",
  "trendId": "2025383938727051697",
  "usersLimit": 10,
  "usersMaxItems": 30
}

Fetch tweets for one specific trend topic:

{
  "inputTargetType": "trend_tweets",
  "trendId": "2025383938727051697",
  "sort": "latest",
  "limit": 10,
  "maxItems": 30
}

Fetch both tweets and relevant users for one specific trend topic:

{
  "inputTargetType": "trend_tweets_and_users",
  "trendId": "2025383938727051697",
  "sort": "top",
  "limit": 10,
  "maxItems": 30,
  "usersLimit": 10,
  "usersMaxItems": 30
}

Do not use this for tweets:

{
  "inputTargetType": "trend_tweets",
  "category": "trending"
}

Trend timeline items now include helper fields you can reuse directly:

{
  "trend_id": "2025383938727051697",
  "trend_slug": "trend-Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide",
  "trend_name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide"
}

Use trend_id as the numeric trend identifier for tweet and relevant-user runs. trend_slug is only a display-style slug derived from the trend item, for example trend-Southampton Stun Arsenal 2-1 to Reach FA Cup Semis.

Example output

{
  "id": "trend-AI agents",
  "rank": null,
  "name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide",
  "trend_url": {
    "url": "twitter://trending/2025383938727051697",
    "urlType": "DeepLink",
    "urlEndpointOptions": []
  },
  "trend_metadata": {
    "domain_context": null,
    "url": {
      "url": "twitter://trending/2025383938727051697",
      "urlType": "DeepLink",
      "urlEndpointOptions": []
    },
    "meta_description": null,
    "name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide"
  },
  "grouped_trends": [],
  "trend_id": "2025383938727051697",
  "trend_name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide",
  "_type": "timelinetrend"
}

Returned fields

For trend timeline items:

• trend_id: numeric trend identifier reused for tweet and relevant-user runs
• trend_name: human-readable trend title
• trend_slug: display-style slug derived from the trend item
• trend_url.url: deep link like twitter://trending/2040024758503477259
• trend_metadata: extra trend metadata from X

For tweet items:

• id, id_str: tweet identifier
• trend_id, trend_name: trend context attached by the Actor
• url, date, user, rawContent: core tweet fields
• replyCount, retweetCount, likeCount, quoteCount: engagement counters
• media, viewCount: media and reach signals when available

For relevant-user items:

• id, id_str: user identifier
• trend_id, trend_name: trend context attached by the Actor
• username, name, followersCount, friendsCount, verified: key profile fields

{
  "id": 1899999999999999999,
  "trend_id": "2025383938727051697",
  "trend_name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide",
  "user": {
    "username": "espn"
  },
  "rawContent": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide ...",
  "_type": "snscrape.modules.twitter.Tweet"
}

{
  "id": 44196397,
  "trend_id": "2025383938727051697",
  "trend_name": "Vikings Receiver Rondale Moore Dies at 25 in Apparent Suicide",
  "username": "elonmusk",
  "name": "Elon Musk",
  "followersCount": 235240499,
  "friendsCount": 1288,
  "verified": true,
  "_type": "snscrape.modules.twitter.User"
}

FAQ

Do I need my own backend or API setup?
No. This Actor is ready to run on Apify, and backend infrastructure is managed by SIMO IT.

Which values can I use for trendId?
For trends, use one of trending, news, sport, entertainment, or a raw timeline id. For tweets and relevant_users, use a numeric trend rest_id from a concrete trend topic.

Can I collect trend data continuously?
Yes. Run the Actor on a schedule and paginate with maxPages.

How do I get the list of available categories first?
Use one of the built-in preset values shown in the Actor: trending, news, sport, entertainment.

How do I get the list of available trends first?
Run the Actor with one preset category. The returned trend items include a deep link such as twitter://trending/2025383938727051697. The numeric suffix is the trend id you can reuse. In the Actor output use trend_id.

How do I get users for a specific trend topic?
First fetch trends from a preset category, then take one concrete numeric trend_id from the returned items and run the Actor with that trendId. In normal usage auto is enough.

How do I get tweets for a specific trend topic? First fetch trends from a preset category, then reuse trend_id. That numeric id is enough to fetch the tweet feed for that trend. Use sort=latest for the freshest posts or sort=top for the ranked feed.