Twitter Tweets Scraper

Twitter/X Monitoring Scraper

Monitor Twitter/X accounts and collect the latest tweets in reverse chronological order.

This Actor is built for teams that need structured Twitter/X data for ongoing monitoring, research, and downstream analytics — without maintaining their own fragile scraping pipeline.

Why use this Actor

• Monitor one or many Twitter/X accounts in a single run
• Collect structured tweet data with engagement metrics, media, entities, and author details
• Export results to JSON, CSV, Excel, HTML, or integrate them into your own workflow
• Save engineering time by using a maintained Twitter/X monitoring actor instead of building your own stack

Best use cases

• Brand monitoring — Track official brand accounts, competitor brands, and public reactions over time
• Competitor tracking — Watch how competitors publish and what gets engagement
• KOL / creator monitoring — Follow founders, journalists, analysts, creators, and niche experts
• Crypto and market intelligence — Track token projects, exchanges, researchers, and security accounts
• News discovery — Watch fast-moving accounts and collect latest tweets for newsroom workflows
• Research pipelines — Build structured tweet datasets for analysis, reporting, and alerting

How it works

1. Add one or more Twitter/X profile URLs
2. Set a since_date to control how far back the monitoring window should go
3. Set the number of results you want to collect
4. Run the Actor
5. Export the dataset or connect it to your downstream workflow

Input

Field	Type	Description
start_urls	Array	One or more Twitter/X profile URLs
since_date	String	Earliest date to collect from, in YYYY-MM-DD format
result_count	String	Maximum number of tweet results to return

Example input

{
  "start_urls": [
    { "url": "https://x.com/elonmusk" },
    { "url": "https://x.com/peckshield" }
  ],
  "since_date": "2026-04-01",
  "result_count": "50"
}

What this Actor returns

The dataset focuses on the fields most useful for monitoring and analysis:

• full_text
• created_at
• favorite_count
• retweet_count
• reply_count
• quote_count
• views_count
• url
• user.name
• user.screen_name

It also includes media/entities when present, so you can use the same dataset for both alerting and richer analysis.

Verification and trust

What you can verify after a run:

• Tweets are returned in reverse chronological order
• Multiple Twitter/X accounts can be monitored in one run
• Output contains structured engagement metrics and author metadata
• Results are exported through the standard Apify dataset

Known limitations

• This Actor is intended for public Twitter/X timeline monitoring, not protected/private content
• Very large runs may take longer because Twitter/X access is a high-friction environment
• Large result counts can be affected by rate limits or platform-side changes
• If no valid live results are available, fallback behavior may be triggered and should be interpreted accordingly

Why the pricing is worth it

Twitter/X data collection is operationally fragile. Access patterns, anti-bot behavior, and extraction logic can change over time.

This Actor helps you avoid maintaining that stack yourself. Instead of building and maintaining your own Twitter/X monitoring pipeline, you get a maintained workflow that focuses on usable structured output.

Sample output

{
  "full_text": "New product launch this week.",
  "created_at": "Wed Mar 06 10:00:39 +0000 2024",
  "favorite_count": 124,
  "retweet_count": 34,
  "reply_count": 11,
  "quote_count": 2,
  "views_count": "160",
  "url": "https://twitter.com/example/status/1765316555607511292",
  "user": {
    "name": "Example Account",
    "screen_name": "example"
  }
}

Feedback

If this Actor saves you time, please leave a rating on Apify Store. Feedback helps prioritize fixes, upgrades, and new monitoring features.

Related Actors

• youtube-user-channel-scraper
• tiktok-videos-watermark-free-scraper

Maintenance

This Actor is actively maintained to preserve monitoring reliability and structured output quality over time.