Instagram Hashtags Extractor (Rich Metadata) ## Overview This actor performs a deep extraction of Instagram hashtag metadata, delivering structured analytics on engagement patterns, geographic distribution, sentiment indicators, and temporal trends. The extraction pipeline ensures data integrity through timestamp verification, external ID tracking, and multi-dimensional validation. Designed for high-fidelity data operations, this tool provides reliable, schema-consistent outputs suitable for downstream analytical workflows and machine learning pipelines. ## Data Dictionary | Field Name | Data Type | Definition | |------------|-----------|------------| | search_id | String | Unique identifier for the extraction session, prefixed with hs_ | | hashtag | String | The target hashtag string queried during extraction | | total_posts | Integer | Cumulative count of posts associated with the hashtag at extraction time | | scraped_at | String (ISO 8601) | UTC timestamp indicating when the data extraction was executed | | external_id | String | External reference identifier for cross-system tracking, prefixed with hscrp_ | | language_code | String | ISO 639-1 two-letter language code representing primary content language | | is_trending | Boolean | Indicator of whether the hashtag is currently classified as trending | | daily_volume | Integer | Estimated number of new posts using this hashtag per 24-hour period | | metrics.avg_engagement_rate | Float | Mean engagement rate (likes + comments / followers) expressed as percentage | | metrics.reach_score | Float | Proprietary metric (0-100) estimating potential audience reach | | metrics.growth_velocity | Float | Rate of hashtag adoption growth, expressed as multiplier over baseline | | top_locations.cities | Array[String] | Top three cities by post volume associated with this hashtag | | top_locations.countries | Array[String] | ISO 3166-1 alpha-2 country codes for top three countries by usage | | top_locations.coordinates.lat | Float | Latitude coordinate of primary geographic centroid | | top_locations.coordinates.lng | Float | Longitude coordinate of primary geographic centroid | | usage_stats.business_accounts | Float | Percentage of posts from business/creator accounts | | usage_stats.personal_accounts | Float | Percentage of posts from personal accounts | | usage_stats.verified_ratio | Float | Ratio of verified accounts using this hashtag (0-1 scale) | | sentiment_analysis.score | Float | Aggregate sentiment score ranging from -1 (negative) to +1 (positive) | | sentiment_analysis.positive_mentions | Integer | Count of posts with positive sentiment indicators | | sentiment_analysis.negative_mentions | Integer | Count of posts with negative sentiment indicators | | related_hashtags | Array[String] | Co-occurring hashtags frequently used alongside the target hashtag | | peak_hours | Array[Integer] | Hours of day (0-23, UTC) with highest posting activity | | content_categories | Array[String] | Classified content themes associated with hashtag usage | | verification_status.is_verified | Boolean | Indicates if the hashtag data has passed quality validation checks | | verification_status.verified_date | String (ISO 8601) | UTC timestamp of when data verification was completed | ## Sample Dataset Below is a sample of the high-fidelity JSON output: json { "search_id": "hs_2025121934982", "hashtag": "instagram-search-hashtags", "total_posts": 145892, "scraped_at": "2025-12-19T14:22:31Z", "external_id": "hscrp_8f29a4d7e6b3c2a1", "language_code": "en", "is_trending": true, "daily_volume": 2341, "metrics": { "avg_engagement_rate": 3.2, "reach_score": 78.5, "growth_velocity": 1.4 }, "top_locations": { "cities": ["New York", "London", "Mumbai"], "countries": ["US", "UK", "IN"], "coordinates": { "lat": 40.7128, "lng": -74.0060 } }, "usage_stats": { "business_accounts": 45.2, "personal_accounts": 54.8, "verified_ratio": 0.12 }, "sentiment_analysis": { "score": 0.67, "positive_mentions": 823, "negative_mentions": 156 }, "related_hashtags": ["socialmedia", "digitalmarketing", "instagramtips"], "peak_hours": [13, 15, 19], "content_categories": ["marketing", "business", "technology"], "verification_status": { "is_verified": true, "verified_date": "2025-11-30T00:00:00Z" } } ## Configuration Parameters To ensure optimal data depth, configure the following: | Parameter | Field Name | Data Type | Required | Description | Example | |-----------|------------|-----------|----------|-------------|---------| | Search Term | query | String | Yes | Hashtag keyword or search term to extract (without # prefix) | insights | ## Analytical Use Cases Sentiment Analysis: Leverage sentiment_analysis object to perform time-series sentiment tracking across marketing campaigns, identifying shifts in audience perception and brand health indicators. Geographic Network Mapping: Utilize top_locations data to construct spatial distribution models, enabling region-specific content strategies and localized campaign optimization. Temporal Pattern Recognition: Apply peak_hours and daily_volume metrics to build predictive models for optimal posting schedules and content calendar planning. Competitive Intelligence: Cross-reference related_hashtags and content_categories to map competitive landscape positioning and identify emerging content opportunities. Longitudinal Studies: Track growth_velocity and is_trending flags over multiple extraction sessions to measure hashtag lifecycle stages and predict virality trajectories. Audience Segmentation: Analyze usage_stats to differentiate B2B versus B2C engagement patterns and tailor content strategies for business versus personal account audiences. ## Technical Limitations Important Considerations: - Data extraction is subject to Instagram's rate limiting policies; sustained high-volume queries may result in temporary access restrictions - total_posts represents a point-in-time snapshot and may not reflect real-time counts due to caching mechanisms - Geographic coordinates represent centroid calculations and should not be interpreted as precise user locations - Sentiment analysis scores are derived from NLP models with approximately 82% accuracy on English-language content; non-English content may exhibit reduced precision - verification_status reflects data quality checks at extraction time; downstream validation is recommended for mission-critical applications - Historical data retention is limited to 90 days; longitudinal studies requiring longer timeframes should implement external archival strategies - related_hashtags array is limited to top 10 co-occurring tags by frequency - API response times may vary between 2-8 seconds depending on hashtag popularity and platform load --- Keywords & Tags: instagram scraper, instagram hashtag scraper, export instagram hashtags, instagram hashtag analytics, instagram data extractor, hashtag analytics instagram, instagram hashtag search tool, extract instagram hashtag data