Tiktok Data Scraper

TikTok Data Scraper API: Scrape TikTok profiles, videos, comments, hashtags, and music

TikTok Data Scraper is a standalone TikTok scraping API Actor on Apify for teams that need to scrape TikTok data reliably and at scale. You can use it as a practical TikTok API alternative to extract public TikTok profiles, follower/following data, video metadata, comments/replies, hashtag posts, music-based posts, playlist posts, and detailed video objects in one workflow.

Target platform: TikTok.

If you also need direct media download pipelines, use the companion Actor: TikTok Video Downloader.

How to scrape TikTok data in 6 steps

1. Open TikTok Data Scraper on Apify and go to the Input tab.
2. Add at least one source list: userUrls, videoUrlsComments, hashtags, musicUrls, playlistIDs, or videoDetailsList.
3. Choose limits (maxUserResults, commentsPerUrl, videosPerHashtag, etc.) or enable scrapeAll... flags.
4. Start the run.
5. Open the run dataset and review results by section (users, comments, hashtags, music, playlists, video_details).
6. Export data as JSON/CSV/Excel or consume it through the Apify API.

Why use this TikTok scraper on Apify?

• Multi-source extraction in one run: users, videos, hashtags, music, playlists, and video details
• Flexible input formats: TikTok URLs, usernames, @handles, numeric IDs, hashtag names
• Good cost control: per-source limits + optional full pagination with scrapeAll...
• Structured output that is easy to map into BI pipelines and automations
• Production-ready platform features: scheduling, logs, webhooks, API-first access, export formats, and integrations

Apify platform advantages

With Apify, this Actor is not just a script. You get:

• Scheduled recurring runs: Schedules
• Programmatic execution and retrieval: Apify API
• Event-driven orchestration: Webhooks
• Easy downstream delivery: Integrations
• Run observability and debugging: Logs
• Dataset export in multiple formats: Dataset API

What can this Actor extract from TikTok?

The Actor writes structured records with context fields such as section, category, and input, plus source payloads under data.

Data group	Example fields
Video metadata	video_id, title, content_desc, cover, duration, create_time
Video performance	play_count, digg_count, comment_count, share_count, download_count, collect_count
Creator/profile data	author.nickname, author.unique_id, user.id, user.verified, profile stats
Comments and replies	text, reply_count, commenter profile info, parent comment linkage
Discovery entities	hashtag/challenge IDs, music IDs, playlist IDs, search results
Workflow context	section, category, input, and source-specific IDs

Real-world use cases

• Influencer discovery and creator benchmarking by niche, region, and engagement
• Trend tracking by hashtags, sounds/music IDs, and playlist clusters
• Competitor monitoring of posting activity, format mix, and engagement velocity
• Comment mining for sentiment analysis and product feedback loops
• Content intelligence pipelines for agencies, media teams, and growth teams

Input example

{
  "userUrls": ["https://www.tiktok.com/@taylorswift", "@billieeilish"],
  "categories": ["videos", "followers", "user_info"],
  "maxUserResults": 100,
  "scrapeAllUserResults": false,

  "videoUrlsComments": ["https://www.tiktok.com/@username/video/7488888888888888888"],
  "commentsPerUrl": 150,
  "scrapeAllComments": false,
  "repliesPerComment": 20,
  "scrapeAllReplies": false,

  "hashtags": ["dance", "https://www.tiktok.com/hashtag/viral"],
  "videosPerHashtag": 120,
  "scrapeAllHashtagVideos": false,
  "hashtagRegion": "US",

  "musicUrls": ["https://www.tiktok.com/music/original-sound-7488888888888888888"],
  "videosPerMusic": 100,
  "scrapeAllMusicVideos": false,

  "playlistIDs": ["7488888888888888888"],
  "videosPerPlaylist": 100,
  "scrapeAllPlaylistVideos": false,

  "videoDetailsList": ["https://www.tiktok.com/@username/video/7488888888888888888"]
}

Output example

You can download the dataset extracted by TikTok Data Scraper in various formats such as JSON, CSV, Excel, XML, or HTML.

[
  {
    "section": "users",
    "category": "videos",
    "input": "https://www.tiktok.com/@taylorswift",
    "user": "taylorswift",
    "userType": "unique_id",
    "data": {
      "video_id": "7488888888888888888",
      "title": "Sample video",
      "play_count": 123456,
      "comment_count": 321,
      "author": {
        "nickname": "Taylor Swift",
        "unique_id": "taylorswift"
      }
    }
  },
  {
    "section": "comments",
    "itemType": "reply",
    "input": "https://www.tiktok.com/@username/video/7488888888888888888",
    "parentCommentId": "7344444444444444444",
    "videoId": "7488888888888888888",
    "data": {
      "text": "Great clip!",
      "reply_count": 0
    }
  }
]

Video walkthrough

For a quick overview of working with Apify Actors and API-based data extraction, you can watch: https://www.youtube.com/watch?v=ViYYDHSBAKM

How much does TikTok scraping cost?

Cost depends on the amount of data you request and run depth.

Main cost drivers:

• Number of input targets across users/videos/hashtags/music/playlists
• Enabled full-pagination switches (scrapeAll...)
• Comments/replies depth and total paginated pages

Practical recommendation: start with smaller limits, validate data shape and quality, then scale. This gives you a predictable estimate for your own cost per 1,000 records.

Other Actors

Actor	Best for
TikTok Video Downloader	Downloading TikTok video assets and building media pipelines

FAQ, legal, and support

Is it legal to scrape TikTok data?

This Actor is intended for publicly available TikTok data and legitimate analytics, research, and automation use cases. You are responsible for compliance with TikTok terms and applicable law.

Important compliance note: scraped output may include personal data. Personal data can be regulated by GDPR (EU), CCPA/CPRA (California), and other privacy laws. You should only process data when you have a lawful basis and a legitimate business purpose. If unsure, consult legal counsel before running production workflows.

I got fewer results than expected. What should I change?

• Increase source-specific limits (maxUserResults, commentsPerUrl, videosPerHashtag, etc.)
• Enable relevant scrapeAll... flags when you need full pagination
• Verify source inputs are valid and public (URLs, usernames, IDs)
• Try narrower batches first, then scale out

Can I run this as an API and automate exports?

Yes. Run via the Apify API, then fetch items from the run dataset endpoint. You can also schedule jobs and push downstream events via webhooks.

Where do I get help or request improvements?

Use the Actor’s Issues tab in Apify Store for bug reports, feature requests, and custom workflow requests.