Twitter (X) Paid Partnership Scraper & Extractor

A specialized, high-performance scraper designed to accurately detect and extract paid partnerships, sponsored content, and commercial advertisements from X (Twitter). By analyzing deep tweet metadata and standard JSON objects, this tool reveals the commercial relationships that standard APIs often miss.

🚀 Key Features

• Deep Metadata Extraction: Bypasses the surface UI to detect official Paid Partnership labels and hidden affiliate_label flags within the tweet's raw data.
• Sponsorship Verification: Identifies promoted_content attributes and invisible commercial relationship tags.
• Semantic Content Analysis: Scans tweet text for compliance keywords and mandatory FTC disclosures (e.g., #ad, #sponsored, #brandpartner, #promo).
• Brand & Sponsor Intelligence: Automatically extracts available details about the linked brand account or affiliate sponsor involved in the collaboration.
• High-Speed Batch Processing: Concurrently process multiple tweet URLs or IDs in a single run, optimized for Apify's infrastructure.
• Developer-Ready JSON Export: Provides clean, structured data ready for seamless integration into compliance dashboards, marketing analytics tools, or brand safety pipelines.

🎯 Ideal Use Cases

• Brand Compliance Audits: Ensure influencers and KOLs are strictly adhering to FTC guidelines and correctly disclosing paid collaborations.
• Influencer Marketing Monitoring: Automatically verify, track, and archive sponsored posts for your marketing campaigns at scale.
• Competitive Ad Intelligence: Reverse-engineer competitor advertising strategies by discovering who they are sponsoring and how they label their partnerships.
• Market & Niche Research: Analyze the saturation and performance of sponsored content within specific industries or targeted hashtags.

📥 Input Configuration

The Actor accepts either raw Tweet IDs or full URLs.

Field	Type	Description
tweetIds	Array	List of target tweet IDs to analyze.
tweetUrls	Array	(Optional) List of full X/Twitter URLs to analyze.

📤 Output Structure

The scraper returns a rich, structured JSON dataset for each processed tweet.

(Here is a sample output demonstrating the extracted metadata):

[
  {
    "tweet_id": "2043777708430414218",
    "url": "[https://x.com/username/status/2043777708430414218](https://x.com/username/status/2043777708430414218)",
    "is_paid_promotion": false,
    "has_disclosure_keywords": false,
    "sponsor_details": null
  },
  {
    "tweet_id": "2034246147318202855",
    "url": "[https://x.com/username/status/2034246147318202855](https://x.com/username/status/2034246147318202855)",
    "is_paid_promotion": true,
    "has_disclosure_keywords": true,
    "detected_keywords": ["#ad", "partner"],
    "sponsor_details": {
      "brand_name": "ExampleBrand",
      "brand_handle": "@ExampleBrand"
    }
  }
]

💡 Support & Feedback

If you need custom features, higher rate limits, or encounter any issues, please feel free to open an issue in the Issues tab.