Twitter (X.com) User Followers Dataset (Full History)

Overview

This actor performs a deep extraction of follower-level data from Twitter (X.com) user accounts, capturing comprehensive profile metrics, engagement statistics, and temporal metadata. The dataset provides high-fidelity snapshots of account follower ecosystems with built-in data quality indicators including authenticity scoring and bot probability metrics. All records are timestamped and versioned to ensure data integrity and enable longitudinal analysis across multiple extraction cycles.

Data Dictionary

Field Name	Data Type	Definition
external_id	String (UUID)	Unique identifier for the extracted record, generated at scrape time
scraped_at	String (ISO 8601)	UTC timestamp indicating when the data extraction occurred
user_stats.follower_count	Integer	Total number of followers associated with the target account at extraction time
user_stats.following_count	Integer	Total number of accounts the target user is following
user_stats.engagement_rate	Float	Calculated engagement percentage based on interactions relative to follower base
user_stats.avg_likes_per_post	Integer	Mean number of likes per post over the most recent 100 posts
profile_data.username	String	Twitter handle without the @ symbol
profile_data.display_name	String	User-defined display name as shown on profile
profile_data.is_verified	Boolean	Indicates whether the account has Twitter verification status (blue checkmark)
profile_data.account_type	String	Classification of account type (e.g., "creator", "business", "personal")
profile_data.created_at	String (ISO 8601)	UTC timestamp of when the Twitter account was originally created
location.country_code	String (ISO 3166-1)	Two-letter country code derived from profile location data
location.region	String	State, province, or regional identifier when available
location.timezone	String (IANA)	IANA timezone identifier based on account settings or inferred location
location.language_code	String (BCP 47)	Primary language code for account content
followers_metadata.growth_rate_30d	Float	Percentage change in follower count over the previous 30-day period
followers_metadata.churn_rate	Float	Percentage of followers lost over the measurement period
followers_metadata.authenticity_score	Float	Proprietary score (0-1) indicating likelihood of genuine follower base
followers_metadata.bot_probability	Float	Calculated probability (0-1) that the account exhibits automated behavior patterns
sentiment_analysis.overall_score	Float	Aggregate sentiment score (-1 to 1) based on recent mentions and interactions
sentiment_analysis.positive_mentions	Integer	Count of positive sentiment mentions in the analysis window
sentiment_analysis.negative_mentions	Integer	Count of negative sentiment mentions in the analysis window
last_updated	String (ISO 8601)	UTC timestamp of the most recent data refresh for this record
is_active	Boolean	Indicates whether the account is currently active and accessible
platform_version	String (Semantic)	Version identifier of the Twitter platform at extraction time
api_version	String (Semantic)	Version of the extraction API used for data collection

Sample Dataset

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

{
  "external_id": "f7d8e9c0-b1a2-4567-8901-234567890abc",
  "scraped_at": "2025-12-21T15:30:22Z",
  "user_stats": {
    "follower_count": 12847,
    "following_count": 892,
    "engagement_rate": 3.2,
    "avg_likes_per_post": 413
  },
  "profile_data": {
    "username": "tech_innovator",
    "display_name": "Alex Chen",
    "is_verified": true,
    "account_type": "creator",
    "created_at": "2023-03-15T08:00:00Z"
  },
  "location": {
    "country_code": "US",
    "region": "California",
    "timezone": "America/Los_Angeles",
    "language_code": "en-US"
  },
  "followers_metadata": {
    "growth_rate_30d": 2.8,
    "churn_rate": 0.5,
    "authenticity_score": 0.94,
    "bot_probability": 0.03
  },
  "sentiment_analysis": {
    "overall_score": 0.78,
    "positive_mentions": 856,
    "negative_mentions": 124
  },
  "last_updated": "2025-12-21T15:30:22Z",
  "is_active": true,
  "platform_version": "2.14.0",
  "api_version": "v3.2"
}

Configuration Parameters

To ensure optimal data depth, configure the following:

Parameter	JSON Field Name	Data Type	Required	Example Value	Description
Username	userId	String	Yes	"elonmusk"	Twitter handle of the target account (without @ symbol)

Analytical Use Cases

Researchers and data scientists can leverage this dataset for multiple analytical workflows:

• Audience Segmentation: Cluster followers by geographic distribution, account age, and engagement patterns to identify distinct audience segments
• Influencer Identification: Filter high-authenticity accounts with strong engagement rates to discover potential collaboration partners
• Bot Detection & Data Quality: Utilize authenticity_score and bot_probability fields to cleanse datasets and ensure analysis is performed on genuine user populations
• Sentiment Analysis: Track sentiment_analysis metrics over time to measure brand perception and campaign effectiveness
• Network Mapping: Construct follower graphs using following_count and relational data to visualize influence networks and information flow patterns
• Longitudinal Studies: Compare scraped_at timestamps across multiple extractions to analyze follower growth trajectories, churn patterns, and engagement evolution
• Lead Generation: Export verified creator accounts with specific engagement thresholds for B2B outreach and partnership development
• Competitive Intelligence: Benchmark follower quality metrics against competitor accounts to inform strategic positioning

Technical Limitations

Important Considerations:

• Rate Limiting: Extraction is subject to Twitter API rate limits. Large follower bases (>100K followers) may require multiple extraction cycles with enforced delays between requests.
• Data Freshness: scraped_at timestamps reflect point-in-time snapshots. Follower counts and engagement metrics may change rapidly; schedule regular extractions for time-series accuracy.
• Private Accounts: Protected accounts cannot be scraped. The is_active field will return false for inaccessible profiles.
• Historical Data Retention: Full history is maintained for 90 days. Records older than 90 days are archived and require separate retrieval processes.
• Authenticity Scoring: The authenticity_score algorithm is probabilistic and should be used as a filtering heuristic rather than absolute truth.
• Geographic Inference: Location data is derived from user-provided profile information and may be incomplete or inaccurate for accounts without explicit location settings.
• API Version Dependencies: Schema structure is tied to api_version. Breaking changes in Twitter's platform may require schema migrations.

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