Twitter User Following Scraper

Twitter User Following Scraper

The Twitter User Following Scraper is a purpose-built tool that extracts the full list of accounts a user follows on X (Twitter) — fast, reliable, and structured for analysis. It solves the hassle of manually collecting “following” relationships by turning any username or URL into a clean dataset. Designed for marketers, developers, data analysts, and researchers, this Twitter following list scraper helps you scale competitor analysis, influencer discovery, and social listening with production-ready automation.

What data / output can you get?

Below are real fields emitted to the Apify dataset as the actor runs. Records are saved incrementally, so you can access results in real time and export to CSV, JSON, or Excel.

Data type	Description	Example value
username	Source username whose following list was scraped	"jordanbpeterson"
id	Twitter (X) user ID of the followed account	"17995040"
name	Display name	"Ben Shapiro"
screen_name	Handle without the @	"benshapiro"
description	Bio/description text	"Daily Wire co-founder, host of @benshapiroshow..."
followers_count	Number of followers	8010425
friends_count	Number of accounts the user is following	486
is_blue_verified	Whether the account has blue verification	true
verified_type	Verification type	null
created_at	Account creation date	"Tue Dec 09 16:40:22 +0000 2008"
profile_url	Full profile URL	"https://x.com/benshapiro"
profile_image_url_https	Profile image URL	"https://pbs.twimg.com/profile_images/..."

Bonus fields included in each record for deeper analysis:

• profile_banner_url, location, url, favourites_count, media_count, statuses_count, listed_count, fast_followers_count, normal_followers_count, profile_image_shape.

Key features

• ⚡️ Real-time data saving
  Results are written to the dataset immediately as pages are processed. Monitor progress and start using data before the run finishes.

• 🧠 Smart proxy fallback
  Automatic proxy handling maximizes success: starts with no proxy, falls back to datacenter, then residential proxies with retry logic when requests are blocked.

• 📦 Bulk username support
  Queue multiple usernames or URLs in one run to export Twitter user following lists at scale.

• 🔎 Flexible input formats
  Provide usernames like "elonmusk" or full URLs like "https://x.com/elonmusk". The scraper extracts the handle automatically.

• 📈 Rate-limited, paginated collection
  Fetches up to 20 users per request with a 1-second delay between pages for stable operation and consistent throughput.

• 🛡 Robust error handling
  Built-in retries, proxy rotation, and response-shape checks help ensure resilient data collection from the Twitter following list API endpoints.

• 💾 Easy exports
  Download Twitter following to CSV, JSON, or Excel directly from the Apify dataset UI for downstream analysis and reporting.

How to use Twitter User Following Scraper - step by step

1. Create or sign in to your Apify account and open the Apify Console.
2. Find and open the “twitter-user-following-scraper” actor.
3. Add input data in the startUrls field:
   • Usernames (e.g., "jordanbpeterson")
   • Full URLs (e.g., "https://x.com/elonmusk" or "twitter.com/billgates")
4. Set maxResults to limit how many followings to scrape per source username (1–10,000; default 200).
5. For best reliability, paste your X/Twitter cookies:
   • authToken (auth_token cookie)
   • ct0 (CSRF cookie; also used as x-csrf-token)
6. Configure proxyConfiguration if needed. By default, the actor starts with no proxy and will automatically fall back to datacenter and then residential proxies if blocked.
7. Click Start. Watch logs for progress updates (e.g., pages fetched, users saved).
8. Open the Dataset tab to see results in real time and export to CSV/JSON/Excel.

Pro Tip: Use this Twitter user following extractor in multi-username runs to build network maps quickly, then export X following lists to CSV for enrichment in your BI or CRM.

Use cases

Use case name	Description
Competitor analysis – map who they follow	Identify partners, media sources, and thought leaders your competitors follow to inform marketing and partnerships.
Influencer discovery – expand outreach	Scrape accounts a Twitter user follows to uncover adjacent creators for targeted campaigns.
Social listening – track signals	Monitor verified and high-follower accounts followed by executives to spot topics and trends.
Network mapping – build relationship graphs	Export Twitter user followings and model follower/friends connections at scale.
Lead generation – enrich profiles	Collect bios, websites, locations, and verification signals from the friends list for prospecting.
Market research – audience interests	Analyze who category leaders follow to understand communities and content preferences.
Data pipeline – automated exports	Schedule runs and export X following lists to CSV/JSON for ingestion into analytics pipelines.
Academic research – behavioral patterns	Study follow dynamics, verified adoption, and network structures using structured outputs.

Why choose Twitter User Following Scraper?

This X following list scraper is engineered for precision, resilience, and scale — purpose-built for production data operations.

• ✅ Real-time, incremental results for immediate access
• 🌐 Intelligent proxy fallback (no proxy → datacenter → residential) with retries
• 📦 Handles multiple usernames and full URLs in a single run
• 🧰 Developer-friendly JSON output with stable field names
• 💾 One-click export to CSV/JSON/Excel from the dataset
• 🛡️ Public data only, with built-in rate limiting and robust error handling
• 🔁 More reliable than brittle browser extensions or manual copy/paste workflows

The result is a dependable Twitter following export tool that streamlines analysis and reduces operational risk.

Is it legal / ethical to use Twitter User Following Scraper?

Yes — when used responsibly. This actor collects data from publicly available following lists and does not access private or password-protected content.

Guidelines for compliant use:

• Scrape only public profiles and publicly visible following relationships.
• Respect Twitter’s Terms of Service and applicable laws (e.g., GDPR, CCPA).
• Avoid using data for spam, harassment, or abusive activities.
• Consult your legal team for edge cases or jurisdiction-specific requirements.

Input parameters & output format

Example JSON input

{
  "startUrls": [
    "jordanbpeterson",
    "https://x.com/elonmusk",
    "twitter.com/billgates"
  ],
  "maxResults": 200,
  "authToken": "",
  "ct0": "",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Input parameters

• startUrls (array, required, default: none)
  • Description: List one or more Twitter usernames (e.g., jordanbpeterson), URLs (e.g., https://x.com/jordanbpeterson), or keywords.
• maxResults (integer, optional, default: 200; min: 1, max: 10000)
  • Description: Maximum number of following users to scrape per username.
• authToken (string, optional, default: "")
  • Description: Your X/Twitter auth_token cookie value. If not provided, the actor will use its built-in default (may stop working over time).
• ct0 (string, optional, default: "")
  • Description: Your X/Twitter ct0 (CSRF) cookie value. If provided, it will also be used as the x-csrf-token header. If not provided, the actor will use its built-in default (may stop working over time).
• proxyConfiguration (object, optional, default: {"useApifyProxy": false})
  • Description: Choose which proxies to use. By default, no proxy is used. If Twitter rejects or blocks the request, it will fallback to datacenter proxy, then residential proxy with 3 retries.

Example JSON output

{
  "username": "jordanbpeterson",
  "id": "17995040",
  "name": "Ben Shapiro",
  "screen_name": "benshapiro",
  "profile_image_url_https": "https://pbs.twimg.com/profile_images/...",
  "profile_banner_url": "https://pbs.twimg.com/profile_banners/...",
  "description": "Daily Wire co-founder, host of @benshapiroshow...",
  "followers_count": 8010425,
  "friends_count": 486,
  "favourites_count": 50,
  "media_count": 8629,
  "statuses_count": 204599,
  "listed_count": 18882,
  "fast_followers_count": 0,
  "normal_followers_count": 8010425,
  "is_blue_verified": true,
  "verified_type": null,
  "created_at": "Tue Dec 09 16:40:22 +0000 2008",
  "profile_url": "https://x.com/benshapiro",
  "location": "",
  "url": "https://t.co/kvSlznhfDe",
  "profile_image_shape": "Circle"
}

Note: Some fields may be empty or null if not present on the public profile (e.g., location, url, verified_type).

FAQ

How many users can I scrape per username?

Up to 10,000 per username, controlled by the maxResults parameter. The scraper fetches up to 20 users per page with a 1-second delay between pages.

Do I need to provide authToken and ct0 cookies?

It’s recommended. The actor includes built-in defaults, but they can expire. Providing your own auth_token and ct0 cookies increases reliability and helps avoid empty or blocked responses.

Does it work without a proxy?

Yes. By default it starts with no proxy. If requests are blocked, the actor automatically falls back to datacenter and then residential proxies with retry logic.

Can I scrape private accounts or hidden following lists?

No. The actor only accesses publicly available following lists. Private accounts or restricted data are not accessible.

Is data saved in real time?

Yes. Each extracted user is pushed to the dataset immediately, enabling you to export Twitter following lists to CSV/JSON/Excel while the run is still in progress.

What happens if Twitter blocks my requests?

The actor detects rejection signals (e.g., 401/403/429) and triggers intelligent proxy fallback: no proxy → datacenter → residential. On residential proxies, it retries up to three times with fresh sessions.

Which fields are included in the output?

Each record includes the source username plus user profile data such as id, name, screen_name, profile and banner images, bio, verification status, counts (followers/friends/statuses/media/favourites), listed_count, fast/normal followers, created_at, location, website url, profile_url, and profile_image_shape.

Can I export results to CSV?

Yes. From the Apify dataset, you can download in CSV, JSON, or Excel. This makes it easy to export X following lists for dashboards, enrichment, or research.

Closing thoughts

Twitter User Following Scraper is built to extract structured “following” data from X reliably and at scale. With real-time records, smart proxy fallback, and clean JSON output, it’s ideal for marketers, developers, analysts, and researchers. Run bulk jobs, export to CSV/JSON/Excel, and plug the results into your analytics or enrichment workflows — then start extracting smarter insights from who your audience and competitors follow.