Twitter User Following Scraper

Twitter User Following Scraper

Twitter User Following Scraper is a fast, reliable Twitter following list scraper that extracts the accounts a user follows on X — including handles, names, bios, links, follower counts, and verification. It solves the tedious work of manually copying follow lists by delivering a structured, export-ready dataset. Built for marketers, developers, data analysts, and researchers, this Twitter user following extractor streams results in real time and supports bulk usernames at scale to power competitor analysis, influencer discovery, outreach, and market research.

What data / output can you get?

Below are the key fields this Twitter following data scraper returns for each followed account. Results save to the Apify dataset as they’re found and can be exported to CSV, JSON, or Excel.

Data field	Description	Example value
id	Twitter user ID	"17995040"
name	Display name	"Ben Shapiro"
screen_name	Twitter handle (without @)	"benshapiro"
profile_url	Full X profile URL	"https://x.com/benshapiro"
profile_image_url_https	Profile image URL	"https://pbs.twimg.com/profile_images/..."
profile_banner_url	Banner image URL	"https://pbs.twimg.com/profile_banners/..."
description	Bio/description text	"Daily Wire co-founder, host of @benshapiroshow..."
followers_count	Number of followers	8010425
friends_count	Number of accounts followed	486
statuses_count	Total number of tweets	204599
is_blue_verified	Blue verification flag	true
created_at	Account creation timestamp	"Tue Dec 09 16:40:22 +0000 2008"

Bonus fields you can use for deeper analysis include: verified_type, location, url (website), favourites_count, media_count, listed_count, fast_followers_count, normal_followers_count, and profile_image_shape.

Key features

• ⚡ Real-time data streaming to dataset
  • Records are saved immediately as they’re scraped so you can monitor progress and download partial results without waiting for the full run.
• 🌐 Smart proxy fallback
  • Automatic progression from no proxy → datacenter → residential (with up to 3 retries for residential) increases success on rate limits and blocks.
• 📦 Bulk username support
  • Process multiple Twitter accounts in a single run — perfect for large-scale research and outreach.
• 🔎 Flexible input formats
  • Accepts usernames and full URLs from x.com or twitter.com; the actor automatically extracts and normalizes handles.
• 📈 Optimized pagination and pacing
  • Pulls ~20 users per request with a 1-second delay between pages, balancing speed and stability on X.
• 🧩 Developer-friendly
  • Runs on the Apify platform and works seamlessly with the Apify API/SDK for pipelines, automation, and integrations.
• 💾 Easy export
  • Export Twitter following to CSV, JSON, or Excel directly from the dataset for spreadsheets, BI tools, and CRMs.
• 🛡️ Production-ready reliability
  • Includes robust error handling, retry logic, and proxy fallback to make this X following list scraper resilient at scale.

How to use Twitter User Following Scraper - step by step

1. Create or log in to your Apify account and open the Apify Console.
2. Find the “twitter-user-following-scraper” actor and open it.
3. Add input data:
   • Enter Twitter usernames or profile URLs in startUrls (one per line or as an array).
   • Set maxResults to cap how many following users to extract per source username (1–10,000; default 200).
   • Optionally, add authToken and ct0 from your browser cookies for higher reliability.
   • Optionally, configure proxyConfiguration (recommended for larger jobs or if you see blocks).
4. Start the run by clicking Start.
5. Watch real-time logs for progress such as “Fetching page 1…” and “Extracted and saved X users…”.
6. Open the OUTPUT tab to see records appear as they’re scraped.
7. Export results to CSV, JSON, or Excel from the dataset when ready.

Pro tip: For the most reliable results on X, provide your X/Twitter auth_token and ct0 cookies in the input. You can also schedule runs to keep a Twitter following tracker updated over time.

Use cases

Use case	Description
Competitor analysis – following graph	Map who competitors follow to identify partners, vendors, talent pools, and communities they monitor.
Influencer discovery & outreach	Extract the following list of key influencers to find aligned creators for campaigns and partnerships.
Lead generation & enrichment	Build targeted lead lists from followed accounts and export Twitter following to CSV for CRM imports.
Market research & trend mapping	Analyze who industry leaders follow to surface emerging topics, tools, and thought leaders.
Network mapping for analysts	Structure follow relationships into graphs for network analysis and segmentation.
Academic & social research	Collect public following lists for studies of information flow and community formation on X.
Monitoring & reporting	Run at intervals to scrape Twitter user following list updates and track network changes over time.

Why choose Twitter User Following Scraper?

Built for precision and reliability, this Twitter following list downloader delivers structured, ready-to-use data with minimal setup.

• ✅ Accurate, structured output with comprehensive profile fields
• 🚀 Scales to large batches with per-username limits up to 10,000
• 🌐 Resilient proxy fallback (no proxy → datacenter → residential with retries)
• 🧑‍💻 Developer access via Apify API and SDK for pipelines and automation
• 🧱 More stable than extension-based or manual copy/paste alternatives
• 💾 Simple exports to CSV/JSON/Excel for spreadsheets and BI tools
• 🔒 Public data only and transparent controls for auth cookies and proxies

In short: a reliable Twitter following export tool that’s production-ready for teams and workflows.

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

Yes — when used responsibly. This tool collects data from publicly available following lists on X/Twitter and does not access private accounts or password-protected content.

Guidelines for compliant use:

• Scrape only public information and respect platform rate limits.
• Review and comply with Twitter’s Terms of Service.
• Ensure adherence to data protection laws such as GDPR and CCPA.
• Use the data ethically and avoid spam or harassment.

For edge cases, confirm requirements with your legal team.

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) — List one or more Twitter usernames (e.g., jordanbpeterson), URLs (e.g., https://x.com/jordanbpeterson), or keywords. Default: none.
• maxResults (integer, optional) — Maximum number of following users to scrape per username. Range: 1–10,000. Default: 200.
• authToken (string, optional) — Your X/Twitter auth_token cookie. Default: "" (uses a built-in default that may stop working over time).
• ct0 (string, optional) — Your X/Twitter ct0 (CSRF) cookie. Also used as x-csrf-token header. Default: "" (uses a built-in default that may stop working over time).
• proxyConfiguration (object, optional) — Proxy settings. By default, no proxy is used. If requests are rejected, the actor falls back to datacenter and then residential proxies with up to 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,
  "statuses_count": 204599,
  "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",
  "favourites_count": 50,
  "media_count": 8629,
  "listed_count": 18882,
  "fast_followers_count": 0,
  "normal_followers_count": 8010425,
  "profile_image_shape": "Circle"
}

Notes on fields:

• username is the source handle whose following list is being exported.
• verified_type can be null, depending on account.
• profile_banner_url, location, and url may be empty or missing if not present on the profile.
• favourites_count, media_count, listed_count, fast_followers_count, normal_followers_count default to 0 if not provided by X.
• profile_url is constructed from screen_name when available.

FAQ

How many users can I scrape per username?

Up to 10,000 per source username, controlled by maxResults. The actor paginates ~20 users per request with a short delay to maintain stability.

Do I need to provide login cookies?

Providing authToken and ct0 cookies is recommended for reliability. The actor includes built-in defaults, but they may stop working over time, and X may return empty responses without valid cookies.

Does it work without a proxy?

Yes. It starts with no proxy by default. If X/Twitter blocks requests, it automatically falls back to a datacenter proxy and then a residential proxy with up to 3 retries.

What formats can I export to?

You can export Twitter following to CSV, JSON, or Excel from the Apify dataset. This makes it easy to move data into spreadsheets, BI tools, or CRMs.

Can I scrape private accounts?

No. The actor only collects data from publicly available following lists. Private accounts’ follow lists are not accessible.

How fast is it?

The actor fetches up to ~20 users per page and waits about 1 second between pages. Throughput depends on the number of usernames, maxResults, network conditions, and X/Twitter response times.

Does it support multiple usernames in one run?

Yes. Add multiple handles or profile URLs to startUrls to run this Twitter following list downloader in bulk.

Can developers integrate this into pipelines?

Yes. Use the Apify API or SDK to run this X user following extractor programmatically and pipe results into your data workflows and automations.

Closing CTA / Final thoughts

Twitter User Following Scraper is built to scrape Twitter user following lists at scale with structured, reliable output. With real-time saving, smart proxy fallback, and export-ready fields, it’s ideal for marketers, researchers, analysts, and developers. Use it as a Twitter following API extractor in your automation stack, export Twitter following to CSV for spreadsheet analysis, or connect it to data pipelines via the Apify API. Start extracting smarter following insights from X today.