Instagram Followers Extractor (Rich Metadata + cookieless) ## Overview This actor performs a deep extraction of Instagram follower data with enriched metadata, delivering structured JSON output optimized for analytical workflows. The extraction pipeline captures account-level attributes, engagement metrics, profile metadata, and content analysis signals without requiring authentication cookies. Data integrity is maintained through versioned schemas and timestamp validation, ensuring reliable downstream processing for segmentation models and audience intelligence systems. ## Data Dictionary | Field Name | Data Type | Definition | |------------|-----------|------------| | external_id | String | Unique identifier for the scrape operation, prefixed with ig_scrape_ | | scraped_at | String (ISO 8601) | UTC timestamp indicating when the extraction was initiated | | account_data.username | String | Instagram handle without the @ symbol | | account_data.display_name | String | Public-facing profile name as displayed on the account | | account_data.follower_count | Integer | Total number of followers at time of extraction | | account_data.following_count | Integer | Total number of accounts the profile follows | | account_data.post_count | Integer | Cumulative number of posts published by the account | | account_data.is_verified | Boolean | Indicates whether the account has Instagram verification badge | | account_data.is_private | Boolean | Indicates whether the account requires follow approval | | account_data.language_code | String (ISO 639-1) | Two-letter language code of primary account content | | account_data.category | String | Instagram business category classification | | engagement_metrics.avg_likes_per_post | Integer | Mean like count calculated across recent posts | | engagement_metrics.avg_comments_per_post | Integer | Mean comment count calculated across recent posts | | engagement_metrics.engagement_rate | Float | Percentage representing (likes + comments) / followers * 100 | | engagement_metrics.follower_growth_rate | Float | Estimated percentage growth in followers over trailing period | | profile_metadata.bio_links | Array[String] | URLs extracted from profile bio section | | profile_metadata.email_hash | String | Hashed representation of contact email if publicly available | | profile_metadata.location.city | String | City name extracted from profile location field | | profile_metadata.location.country_code | String (ISO 3166-1) | Two-letter country code | | profile_metadata.location.timezone | String | IANA timezone identifier for the profile location | | content_analysis.post_frequency | Float | Average number of posts published per week | | content_analysis.top_hashtags | Array[String] | Most frequently used hashtags across recent content | | content_analysis.sentiment_score | Float | Normalized sentiment score ranging from -1.0 (negative) to 1.0 (positive) | | content_analysis.audience_credibility | Float | Calculated score (0.0-1.0) indicating follower authenticity | | last_updated | String (ISO 8601) | UTC timestamp of the most recent data refresh | | version | String (Semantic) | Schema version following semver specification | ## Sample Dataset Below is a sample of the high-fidelity JSON output: json { "external_id": "ig_scrape_789012345678901", "scraped_at": "2025-12-19T12:00:00Z", "account_data": { "username": "travel_enthusiast", "display_name": "Travel & Adventure", "follower_count": 45678, "following_count": 892, "post_count": 1243, "is_verified": true, "is_private": false, "language_code": "en", "category": "Travel & Tourism" }, "engagement_metrics": { "avg_likes_per_post": 2341, "avg_comments_per_post": 89, "engagement_rate": 5.12, "follower_growth_rate": 2.3 }, "profile_metadata": { "bio_links": ["linktr.ee/travel_enthusiast"], "email_hash": "b4d8c7e2f1a9", "location": { "city": "London", "country_code": "GB", "timezone": "GMT" } }, "content_analysis": { "post_frequency": 4.2, "top_hashtags": ["travel", "adventure", "photography"], "sentiment_score": 0.78, "audience_credibility": 0.85 }, "last_updated": "2025-12-19T11:55:23Z", "version": "2.1.0" } ## Configuration Parameters To ensure optimal data depth, configure the following: | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | username | String | Yes | Instagram username to extract follower data from (without @ prefix) | domnique | ## Analytical Use Cases Researchers and data scientists can leverage this structured dataset for: - Audience Segmentation: Cluster followers by engagement patterns, location, and content affinity to identify high-value micro-segments for targeted campaigns - Influencer Vetting: Validate influencer authenticity through audience credibility scores and engagement rate benchmarking against category norms - Sentiment Analysis: Aggregate sentiment scores across follower bases to assess brand perception and content resonance - Network Mapping: Construct follower graphs to identify community structures, opinion leaders, and cross-pollination opportunities - Longitudinal Studies: Track follower growth trajectories, engagement decay curves, and content strategy effectiveness over time - Competitive Intelligence: Compare engagement metrics and audience demographics across competitor accounts within the same category ## Technical Limitations Important Considerations: - Extraction depth is limited to publicly accessible profile data; private accounts return only basic metadata (username, follower count, verification status) - Engagement metrics are calculated from the most recent 12-50 posts depending on account activity; historical data beyond this window is not captured - Rate limiting is enforced at 100 profiles per hour to maintain platform compliance; batch operations should implement exponential backoff - Email hashes are only available when contact information is explicitly displayed in the bio; approximately 15-20% of profiles include this field - Sentiment scores utilize NLP models trained on English-language content; accuracy degrades for non-Latin scripts and mixed-language posts - Data retention policy maintains raw extraction records for 90 days; archived datasets are available upon request for compliance auditing - Schema versioning follows semantic versioning; breaking changes increment the major version and require pipeline updates --- Keywords & Tags: instagram scraper, instagram followers scraper, instagram data extractor, instagram follower export, social media scraping tool, instagram scraping api, lead generation