Linkedin Post Comments,Replies,Engagements Scraper | No Cookies

🚀 Batch LinkedIn Post Comments & Replies Scraper Extract comments, replies, and engagement metrics from LinkedIn posts including author details, reaction counts, timestamps, and nested replies. ### For other LinkedIn actors, check: https://apify.com/apimaestro ## ✨ Key Features - No account needed: Don't risk your account security by sharing your cookies and don't get your account restricted or banned! - Comments and nested replies from LinkedIn posts - Author details for each comment and reply - Reaction counts by type (likes, appreciations, etc.) - Comment timestamps (both absolute and relative) - Support for multiple post formats and IDs - Sorting options (most relevant or most recent) - Ability to process posts in batches very fast ## 🔧 Usage ### Input Formats The actor accepts various LinkedIn post identifier formats: - Numeric post IDs: 7302346926123798528 - Activity URLs: https://www.linkedin.com/feed/update/urn:li:activity:7302346926123798528/ - Full post URLs: https://www.linkedin.com/posts/username_title-activity-7302346926123798528-dMnz ### Sorting Options You can choose how comments are sorted: - Most relevant (default): Shows the comments LinkedIn considers most engaging first - Most recent: Shows the newest comments first (may not always work for all posts) ## Pagination Support Each run returns up to 100 post data per page. Page Number is the field used for pagination. It's 1 by default. - Page 1: Returns results 1-100 - Page 2: Returns results 101-200 - Page 3: Returns results 201-300 - And so on... ## Output Structure The actor produces structured data for each comment and reply: json { "comment_id": "7302375502034411520", "text": "This is a great point! Healthcare professionals need...", "posted_at": { "timestamp": 1626782941000, "date": "2023-07-20 12:49:01", "relative": "2d" }, "is_edited": false, "is_pinned": false, "comment_url": "https://www.linkedin.com/feed/update/...", "comment_type": "comment", "author": { "name": "John Smith", "headline": "Healthcare Professional | Digital Health Advocate", "profile_url": "https://www.linkedin.com/in/johnsmith/", "profile_picture": "https://media.licdn.com/dms/image/..." }, "stats": { "total_reactions": 25, "reactions": { "like": 20, "appreciation": 3, "empathy": 2, "interest": 0, "praise": 0 }, "comments": 3 }, "post_input": "7302346926123798528" } For replies, additional fields are included: json { "comment_type": "reply", "parent_comment_id": "7302375502034411520" } ## Use Cases - Content analysis and sentiment tracking - Engagement monitoring for social media managers - Competitive intelligence gathering - Market research and consumer feedback analysis - Influencer research and audience analysis