Instagram User Info Extractor (Rich Metadata)

Overview

This actor performs a deep extraction of Instagram user profile data, capturing comprehensive metadata across identity, engagement, content, and behavioral dimensions. The extraction pipeline prioritizes data integrity through structured validation and timestamp-based provenance tracking. Output conforms to a normalized schema optimized for analytical workflows, ensuring consistency across large-scale data collection operations.

Data Dictionary

Field Name	Data Type	Definition
user_id	String	Platform-assigned unique identifier for the Instagram account
username	String	Public handle used for account identification and URL routing
external_id	String	System-generated external reference ID for cross-platform tracking
scraped_at	String (ISO 8601)	UTC timestamp indicating exact moment of data extraction
display_name	String	User-defined profile name displayed on the account page
is_verified	Boolean	Verification status indicating platform-authenticated account (blue checkmark)
is_private	Boolean	Privacy setting indicating whether account content requires follow approval
language_code	String	ISO language-region code representing primary account language
follower_count	Integer	Total number of accounts following this user at extraction time
following_count	Integer	Total number of accounts this user follows at extraction time
post_count	Integer	Cumulative number of posts published by the account
engagement_metrics.avg_likes	Integer	Mean number of likes per post calculated across recent content
engagement_metrics.avg_comments	Integer	Mean number of comments per post calculated across recent content
engagement_metrics.engagement_rate	Float	Percentage representing (likes + comments) / followers * 100
engagement_metrics.reach_estimate	Integer	Estimated unique accounts reached per post based on engagement patterns
profile_metadata.business_category	String	Instagram-defined business vertical classification
profile_metadata.account_type	String	Account classification (PERSONAL, CREATOR, BUSINESS)
profile_metadata.joined_date	String (ISO 8601 Date)	Date when the account was created on Instagram
profile_metadata.last_post_timestamp	String (ISO 8601)	UTC timestamp of the most recent content publication
location_data.country_code	String	ISO 3166-1 alpha-2 country code derived from profile location
location_data.city	String	City name extracted from profile location metadata
location_data.timezone	String	IANA timezone identifier associated with account location
content_analysis.primary_topics	Array[String]	Machine-extracted topic tags representing dominant content themes
content_analysis.sentiment_score	Float	Normalized sentiment score (0.0-1.0) derived from caption analysis
content_analysis.authenticity_score	Float	Computed authenticity metric (0.0-1.0) based on engagement patterns and follower quality

Sample Dataset

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

{
  "user_id": "839275610384",
  "username": "tech_influencer_92",
  "external_id": "inst_usr_8392756103840001",
  "scraped_at": "2025-12-19T15:22:31Z",
  "display_name": "Tech Insights Daily",
  "is_verified": true,
  "is_private": false,
  "language_code": "en_US",
  "follower_count": 245631,
  "following_count": 892,
  "post_count": 1432,
  "engagement_metrics": {
    "avg_likes": 15234,
    "avg_comments": 342,
    "engagement_rate": 6.2,
    "reach_estimate": 89000
  },
  "profile_metadata": {
    "business_category": "TECHNOLOGY",
    "account_type": "CREATOR",
    "joined_date": "2019-03-15",
    "last_post_timestamp": "2025-12-18T22:15:43Z"
  },
  "location_data": {
    "country_code": "US",
    "city": "San Francisco",
    "timezone": "America/Los_Angeles"
  },
  "content_analysis": {
    "primary_topics": ["tech", "programming", "ai"],
    "sentiment_score": 0.87,
    "authenticity_score": 0.92
  }
}

Configuration Parameters

To ensure optimal data depth, configure the following:

Parameter	Type	Required	Description	Example
username	String	Yes	Instagram username (handle) to extract profile data from. Exclude @ symbol.	domnique

Analytical Use Cases

Competitive Intelligence: Benchmark engagement metrics and content strategies across competitor accounts to identify performance gaps and opportunities.

Audience Segmentation: Cluster user profiles by engagement patterns, content topics, and demographic signals for targeted campaign development.

Influencer Vetting: Assess authenticity scores and engagement rates to identify high-quality partnership candidates and detect fraudulent accounts.

Sentiment Analysis: Track sentiment trends over time to measure brand perception and content resonance within specific audience segments.

Network Mapping: Construct follower-following graphs to identify community structures, key opinion leaders, and information diffusion pathways.

Longitudinal Studies: Monitor profile evolution metrics (follower growth, engagement shifts, content topic drift) to understand platform dynamics and user behavior patterns.

Lead Generation: Export verified business accounts with specific engagement thresholds and location criteria for B2B prospecting workflows.

Technical Limitations

Important Considerations:

• Extraction accuracy depends on account privacy settings; private accounts return limited metadata fields only.
• Engagement metrics represent point-in-time snapshots and may not reflect historical performance trends.
• Content analysis fields (sentiment, authenticity, topics) are derived metrics subject to model confidence thresholds.
• Rate limiting applies at 100 profile extractions per hour to maintain platform compliance.
• Data retention window is 90 days; historical extractions beyond this period are not guaranteed.
• Follower/following counts may experience ±2% variance due to platform caching mechanisms.
• Location data availability depends on user-provided profile information; null values are common.
• Business category and account type classifications reflect Instagram's taxonomy at extraction time and may change.

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