Tiktok User Followers Dataset (Full History)

Overview

This actor performs a deep extraction of TikTok follower data, capturing comprehensive user profiles with full historical context. The dataset provides structured, high-fidelity records of follower accounts including demographic information, engagement metrics, and temporal metadata. Data integrity is maintained through timestamped snapshots and validated field structures, ensuring reliability for downstream analytical workflows.

Data Dictionary

Field Name	Data Type	Definition
user_id	String	Platform-native unique identifier for the TikTok user account
external_id	String	System-generated external reference ID with prefix notation for cross-platform tracking
scraped_at	String (ISO 8601)	UTC timestamp indicating when the data extraction occurred
username	String	User's handle/username without @ prefix
display_name	String	User's public-facing display name as shown on profile
is_verified	Boolean	Indicates whether the account has official platform verification (blue checkmark)
language_code	String	ISO 639-1 language code with regional variant (e.g., en-US)
follower_count	Integer	Total number of accounts following this user at time of extraction
following_count	Integer	Total number of accounts this user follows
account_type	String	Classification of account category (e.g., creator, business, personal)
location.city	String	User's declared city of residence
location.country	String	User's declared country of residence
location.timezone	String	IANA timezone identifier for user's location
location.geo.latitude	Float	Geographic latitude coordinate
location.geo.longitude	Float	Geographic longitude coordinate
engagement_metrics.avg_likes	Integer	Mean number of likes per post across recent content
engagement_metrics.avg_comments	Integer	Mean number of comments per post across recent content
engagement_metrics.engagement_rate	Float	Calculated engagement rate as percentage (interactions/followers × 100)
engagement_metrics.weekly_growth	Float	Percentage change in follower count over trailing 7-day period
profile_stats.posts_count	Integer	Total number of posts published by the user
profile_stats.lists_included	Integer	Number of curated lists featuring this user
profile_stats.mentions_count	Integer	Cumulative count of mentions received across platform
account_metadata.created_at	String (ISO 8601)	UTC timestamp of account creation date
account_metadata.last_active	String (ISO 8601)	UTC timestamp of most recent user activity
account_metadata.is_private	Boolean	Indicates whether the account has privacy restrictions enabled
account_metadata.has_highlights	Boolean	Indicates presence of story highlights on profile
sentiment_score	Float	Normalized sentiment score (0.0-1.0) derived from profile content analysis

Sample Dataset

Below is a sample of the high-fidelity JSON output:

{
  "user_id": "874520196834",
  "external_id": "usr_874520196834_f29d8",
  "scraped_at": "2025-12-19T15:22:31Z",
  "username": "tech_innovator",
  "display_name": "Sarah Chen",
  "is_verified": true,
  "language_code": "en-US",
  "follower_count": 28451,
  "following_count": 892,
  "account_type": "creator",
  "location": {
    "city": "San Francisco",
    "country": "United States",
    "timezone": "America/Los_Angeles",
    "geo": {
      "latitude": 37.7749,
      "longitude": -122.4194
    }
  },
  "engagement_metrics": {
    "avg_likes": 1245,
    "avg_comments": 89,
    "engagement_rate": 4.37,
    "weekly_growth": 2.8
  },
  "profile_stats": {
    "posts_count": 892,
    "lists_included": 45,
    "mentions_count": 1267
  },
  "account_metadata": {
    "created_at": "2023-03-15T08:00:00Z",
    "last_active": "2025-12-18T22:15:43Z",
    "is_private": false,
    "has_highlights": true
  },
  "sentiment_score": 0.78
}

Configuration Parameters

To ensure optimal data depth, configure the following:

Parameter	Field Name	Required	Format	Example
TikTok Secure User ID	secUid	Yes	Alphanumeric string (Base64-encoded identifier)	MS4wLjABAAAAqB08cUbXaDWqbD6MCga3RbGTuhfO4EsHayBYx08NDrN7IE3kQiRDNNN6YwyfH6_6

Note: The secUid parameter is the platform's secure user identifier, distinct from the public-facing username. This value can be extracted from TikTok profile URLs or API responses.

Analytical Use Cases

This dataset supports multiple research and business intelligence applications:

• Audience Segmentation: Cluster followers by geographic distribution, engagement patterns, and account characteristics to identify distinct audience segments
• Influencer Identification: Filter verified creators with high engagement rates to discover collaboration candidates within specific niches
• Network Mapping: Construct follower graphs to analyze community structures, identify key opinion leaders, and map influence propagation paths
• Longitudinal Studies: Track follower growth trajectories, engagement metric evolution, and account lifecycle patterns over time
• Sentiment Analysis: Aggregate sentiment scores across follower cohorts to assess brand perception and audience disposition
• Demographic Profiling: Analyze location, language, and account type distributions to understand audience composition
• Lead Generation: Export high-engagement followers matching specific criteria for targeted outreach campaigns
• Competitive Intelligence: Compare follower bases across competitor accounts to identify market positioning and audience overlap

Technical Limitations

Important Considerations:

• Rate Limiting: TikTok API enforces request throttling; bulk extractions may require batched execution with delays between requests
• Data Freshness: Follower counts and engagement metrics represent point-in-time snapshots; real-time accuracy degrades as data ages
• Private Accounts: Users with is_private: true return limited profile information; follower lists may be inaccessible
• Geographic Precision: Location data relies on user-declared information; coordinates may represent city centroids rather than precise locations
• Engagement Calculations: Average metrics are computed from recent post samples (typically trailing 30 days); historical content is not included
• Sentiment Scoring: Sentiment values are algorithmically derived and may not reflect nuanced contextual meaning
• Data Retention: Historical snapshots are preserved for 90 days; longitudinal analysis requires scheduled recurring extractions
• Field Availability: Not all fields populate for every user; business accounts may expose additional metadata not present in personal profiles

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