Instagram Location Posts Extractor (Rich Metadata) ## Overview This actor performs a deep extraction of location-tagged Instagram posts with comprehensive metadata enrichment. The extraction pipeline captures geospatial coordinates, engagement statistics, sentiment indicators, and temporal activity patterns for specified location queries. Data integrity is maintained through verification checksums and timestamp validation. The output schema is designed for high-fidelity analytical workflows requiring structured, normalized location intelligence. ## Data Dictionary | Field Name | Data Type | Definition | |------------|-----------|------------| | location_id | String | Unique Instagram identifier for the location entity | | name | String | Human-readable location name as displayed on Instagram | | external_id | String | External reference identifier for cross-platform location matching | | scraped_at | String (ISO 8601) | UTC timestamp indicating when the extraction was performed | | coordinates.latitude | Float | Geographic latitude coordinate in decimal degrees | | coordinates.longitude | Float | Geographic longitude coordinate in decimal degrees | | coordinates.accuracy | Float | Confidence score (0-1) for coordinate precision | | metadata.place_type | String | Classification of location type (e.g., park, restaurant, landmark) | | metadata.city | String | City name where the location is situated | | metadata.country_code | String | ISO 3166-1 alpha-2 country code | | metadata.language_code | String | ISO 639-1 language code for primary location language | | metadata.timezone | String | IANA timezone identifier for the location | | stats.total_posts | Integer | Cumulative count of posts tagged at this location | | stats.unique_users | Integer | Count of distinct users who have posted at this location | | stats.average_engagement | Float | Mean engagement rate (likes + comments) per post | | stats.peak_hours | Array[Integer] | Hours of day (0-23) with highest posting activity | | current_activity.active_users | Integer | Number of users currently active at the location | | current_activity.live_stories | Integer | Count of active Instagram Stories from this location | | current_activity.trending_score | Float | Normalized trending metric (0-1) based on recent activity velocity | | verification.is_verified | Boolean | Indicates if the location has been verified by Instagram | | verification.verified_date | String (ISO 8601) | Date when location verification was completed | | verification.verification_source | String | Source system that performed the verification | | sentiment_analysis.current_score | Float | Real-time sentiment score (-1 to 1) derived from recent posts | | sentiment_analysis.weekly_average | Float | Rolling 7-day average sentiment score | | sentiment_analysis.sample_size | Integer | Number of posts analyzed for sentiment calculation | | last_updated | String (ISO 8601) | UTC timestamp of the most recent data refresh | | is_active | Boolean | Indicates if the location is currently accepting new posts | | category_tags | Array[String] | Taxonomy tags for location categorization and filtering | | search_weight | Float | Relevance score (0-1) for search ranking algorithms | | monthly_checkins | Integer | Count of user check-ins at this location in the past 30 days | ## Sample Dataset Below is a sample of the high-fidelity JSON output: json { "location_id": "567891234567890", "name": "Central Park, New York", "external_id": "loc_cp_ny_45678901234", "scraped_at": "2025-12-19T12:00:00Z", "coordinates": { "latitude": 40.7829, "longitude": -73.9654, "accuracy": 0.95 }, "metadata": { "place_type": "park", "city": "New York", "country_code": "US", "language_code": "en", "timezone": "America/New_York" }, "stats": { "total_posts": 2456789, "unique_users": 789456, "average_engagement": 342.8, "peak_hours": [14, 17, 20] }, "current_activity": { "active_users": 1234, "live_stories": 45, "trending_score": 0.87 }, "verification": { "is_verified": true, "verified_date": "2024-03-15T00:00:00Z", "verification_source": "instagram_places" }, "sentiment_analysis": { "current_score": 0.76, "weekly_average": 0.82, "sample_size": 5000 }, "last_updated": "2025-12-19T11:45:23Z", "is_active": true, "category_tags": ["outdoors", "landmark", "tourism", "nature"], "search_weight": 0.95, "monthly_checkins": 45678 } ## Configuration Parameters To ensure optimal data depth, configure the following: | Parameter | Field Name | Data Type | Required | Description | Example | |-----------|------------|-----------|----------|-------------|---------| | Location Query | locationQuery | String | Yes | Valid Instagram location name for targeted extraction | "California" | ## Analytical Use Cases Geospatial Engagement Analysis: Researchers can correlate coordinates with stats.average_engagement to identify high-performing geographic clusters and optimize location-based marketing campaigns. Temporal Activity Profiling: The stats.peak_hours array enables time-series analysis of user behavior patterns, supporting optimal content scheduling strategies for maximum visibility. Sentiment Trend Monitoring: Longitudinal studies can track sentiment_analysis.weekly_average over time to detect shifts in public perception associated with specific locations or events. Competitive Location Intelligence: Cross-referencing stats.unique_users and monthly_checkins across multiple locations provides comparative benchmarking for venue popularity and market penetration. Real-Time Opportunity Detection: The current_activity.trending_score metric identifies emerging hotspots for time-sensitive marketing interventions and influencer partnerships. Taxonomy-Based Segmentation: The category_tags array facilitates cohort analysis and audience segmentation based on location preferences and behavioral affinities. ## Technical Limitations Important Considerations: - Instagram API rate limits restrict extraction to approximately 200 location queries per hour per authentication token - Historical data retention is limited to the most recent 90 days of activity metrics; older stats values may reflect cumulative totals only - The sentiment_analysis module requires a minimum sample_size of 100 posts for statistical validity; locations with fewer posts will return null sentiment scores - Coordinate accuracy below 0.80 indicates potential geocoding ambiguity and should be validated against external geospatial databases - The current_activity object reflects a 15-minute rolling window and may not capture instantaneous spikes in user engagement - Private or restricted locations may return incomplete metadata fields; verification.is_verified should be checked before downstream processing - The trending_score algorithm is proprietary and may not align with Instagram's internal trending calculations --- Keywords & Tags: instagram scraper, instagram location posts, export instagram posts, scrape instagram by location, instagram data extraction, lead generation instagram, location-based instagram data