Facebook Page Reviews Extractor (Rich Metadata)cookieless

"# Facebook Page Details Extractor (Rich Metadata)

Overview

This actor performs a deep extraction of Facebook page metadata, engagement signals, and content attributes through cookieless scraping methodology. The extractor returns structured JSON output with guaranteed schema consistency, enabling reliable downstream analytics and data warehousing operations. Data integrity is maintained through timestamp validation, type enforcement, and null-handling protocols.

Data Dictionary

Field Name	Data Type	Definition
page_id	String	Unique internal identifier for the Facebook page entity
external_id	String	Composite external reference ID combining timestamp, operation code, and page identifier
url	String	Canonical URL of the extracted Facebook page
scraped_at	String (ISO 8601)	UTC timestamp indicating when the extraction operation was executed
last_modified	String (ISO 8601)	UTC timestamp of the most recent content modification on the page
title	String	Primary page title or headline text
content_type	String	Classification of content format (e.g., article, video, post)
language_code	String	ISO 639-1 language code with optional region identifier
is_verified	Boolean	Indicates whether the page has official verification status (blue check)
word_count	Integer	Total number of words in the primary content body
metadata.author_id	String	Unique identifier for the content author or page administrator
metadata.section	String	Content categorization or section taxonomy
metadata.reading_time	Integer	Estimated reading duration in minutes
metadata.content_tier	String	Access level classification (e.g., free, premium, subscriber-only)
engagement_metrics.views	Integer	Total number of page views recorded
engagement_metrics.shares	Integer	Count of share actions across all platforms
engagement_metrics.bookmarks	Integer	Number of times the page was bookmarked or saved
engagement_metrics.time_on_page	Integer	Average time spent on page in seconds
seo_data.meta_description	String	SEO meta description tag content
seo_data.keywords	Array[String]	List of SEO keywords associated with the page
seo_data.canonical_url	String	Canonical URL specified for search engine indexing
sentiment_score	Float	Normalized sentiment analysis score ranging from -1.0 (negative) to 1.0 (positive)
readability_score	Integer	Flesch-Kincaid or similar readability index score
has_paywall	Boolean	Indicates presence of paywall or content restriction mechanism
revision_count	Integer	Number of editorial revisions or updates to the content

Sample Dataset

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

{
  ""page_id"": ""p_789456123"",
  ""external_id"": ""2025122001_PGEX_789456123"",
  ""url"": ""https://example.com/page/789456123"",
  ""scraped_at"": ""2025-12-20T08:15:32Z"",
  ""last_modified"": ""2025-12-19T23:45:12Z"",
  ""title"": ""Advanced Data Analytics Overview"",
  ""content_type"": ""article"",
  ""language_code"": ""en-US"",
  ""is_verified"": true,
  ""word_count"": 2456,
  ""metadata"": {
    ""author_id"": ""auth_45678"",
    ""section"": ""Technology"",
    ""reading_time"": 12,
    ""content_tier"": ""premium""
  },
  ""engagement_metrics"": {
    ""views"": 15234,
    ""shares"": 892,
    ""bookmarks"": 445,
    ""time_on_page"": 325
  },
  ""seo_data"": {
    ""meta_description"": ""Comprehensive guide to modern data analytics"",
    ""keywords"": [""analytics"", ""data science"", ""machine learning""],
    ""canonical_url"": ""https://example.com/analytics-guide""
  },
  ""sentiment_score"": 0.78,
  ""readability_score"": 42,
  ""has_paywall"": true,
  ""revision_count"": 3
}

Configuration Parameters

To ensure optimal data depth, configure the following:

Parameter	JSON Field Name	Data Type	Required	Example Value	Description
Page URL	pageUrl	String	Yes	https://www.facebook.com/facebook	Fully qualified URL of the target Facebook page to extract

Analytical Use Cases

Sentiment Analysis: Leverage sentiment_score and readability_score fields to perform content quality assessments and audience alignment studies across page portfolios.

Engagement Benchmarking: Utilize engagement_metrics object to establish performance baselines, identify high-performing content patterns, and calculate engagement rate distributions for competitive intelligence.

Content Lifecycle Tracking: Combine scraped_at, last_modified, and revision_count fields to construct temporal datasets for longitudinal content evolution studies and editorial velocity analysis.

Lead Qualification Scoring: Cross-reference is_verified, content_tier, and engagement signals to build predictive models for B2B lead prioritization and account-based marketing segmentation.

SEO Competitive Analysis: Extract seo_data structures across competitor pages to perform keyword gap analysis, canonical URL mapping, and meta description optimization research.

Technical Limitations

Important Considerations:

• Extraction operates without authentication cookies; data availability is limited to publicly accessible page content only
• Rate limiting is enforced at 100 requests per minute to maintain platform compliance and prevent IP throttling
• engagement_metrics values represent point-in-time snapshots and do not include historical trend data
• sentiment_score calculation is performed using rule-based NLP models; accuracy may vary for domain-specific or technical content
• Nested metadata fields may return null values if the source page lacks structured data markup
• Data retention policy: raw extraction logs are purged after 30 days; only processed JSON outputs are persisted long-term
• last_modified timestamp accuracy depends on source page HTTP headers; fallback to scraped_at if unavailable

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Keywords & Tags: web scraping tool, web scraper, data extraction tool, export website data, product data scraper, lead generation scraping, price data scraper"