{ "openapi": "3.0.1", "info": { "title": "LinkedIn Groups Scraper - Members, Admins & Posts [No Login] ✅", "description": "Search LinkedIn Groups by keyword and get full profiles with admins, plus extract group posts and their active-poster authors as a ready-to-enrich member list. No login, no cookies. 4 modes cover discovery, targeted fetch, and posts. Time filter up to 5 years back. 0.20% failure rate.", "version": "0.0", "x-build-id": "vfCmzSzGVrHJTq51j" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/unseenuser~LinkedIn-Groups-Scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-unseenuser-LinkedIn-Groups-Scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/unseenuser~LinkedIn-Groups-Scraper/runs": { "post": { "operationId": "runs-sync-unseenuser-LinkedIn-Groups-Scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/unseenuser~LinkedIn-Groups-Scraper/run-sync": { "post": { "operationId": "run-sync-unseenuser-LinkedIn-Groups-Scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "What do you want to do?", "enum": [ "search_and_get", "search_groups", "get_group", "group_posts" ], "type": "string", "description": "Pick the operation that matches your goal.", "default": "search_and_get" }, "searchKeywords": { "title": "Search keywords", "type": "string", "description": "Industry, role, technology, or niche — anything LinkedIn search accepts.\n\n• 'RevOps' · 'Fintech' · 'Generative AI' · 'Sales Operations' · 'Pharma Marketing'\n\nSpecific keywords beat broad ones — 'B2B SaaS Founders' returns better-targeted groups than 'business'." }, "maxResults": { "title": "How many groups to return (0 = fetch everything, no cap)", "minimum": 0, "type": "integer", "description": "Cap on the number of groups returned by the search.\n\n**Set to 0 to fetch every matching group with no artificial cap.** Any positive number is honored as-is. Natural stops still apply: LinkedIn's pagination ends, an internal 30-minute safety timer trips, or your plan's item cap fires (free-plan runs stop at 5 items).\n\n• **Search & Get Full Profiles:** keep this LOW (5-25) unless you really want everything. Each group triggers a full profile fetch.\n• **Search Groups Only:** safe to set high (or 0 for all). Results are cheap discovery.", "default": 0 }, "groupInputs": { "title": "Group URLs or IDs", "uniqueItems": true, "type": "array", "description": "Paste LinkedIn group URLs or numeric IDs — one per line. Both formats are accepted and auto-detected, whitespace is trimmed, duplicates removed.\n\nExamples:\n• `https://www.linkedin.com/groups/1898033/`\n• `https://www.linkedin.com/groups/1898033/about/`\n• `1898033`\n\nDon't know the IDs yet? Use 'Search Groups Only' first to discover them, then paste the IDs here.", "items": { "type": "string" } }, "maxPostsPerGroup": { "title": "Posts per group (0 = every available post, no cap)", "minimum": 0, "type": "integer", "description": "Maximum posts to scrape from each group.\n\n**Set to 0 to pull every available post per group with no artificial cap.** Any positive number is honored as-is. Natural stops still apply: LinkedIn's pagination ends per group, an internal 30-minute safety timer trips, or your plan's item cap fires (free-plan runs stop at 5 items).\n\nMultiply this by the number of groups for total cost.", "default": 0 }, "sortBy": { "title": "Sort posts by", "enum": [ "relevance", "date" ], "type": "string", "description": "How to order the posts within each group.", "default": "relevance" }, "timeWindow": { "title": "Time window — only posts from the past…", "enum": [ "", "1h", "24h", "week", "month", "3months", "6months", "year" ], "type": "string", "description": "Restrict posts to a recent window. Leave on 'No limit' to get the broadest catch.\n\nLinkedIn-side filters (faster): Past 24 hours, Past week, Past month.\nUpstream-side filters (finer control): Past hour, Past 3 months, Past 6 months, Past year.", "default": "" }, "extractMembers": { "title": "Also extract members (admins + active posters)", "type": "boolean", "description": "When ON, the Actor produces a dedicated **members** dataset alongside the main output, with one row per person:\n\n• Group admins (from get_group / search_and_get) — always available, no extra API cost.\n• Active posters (from group_posts) — the authors of public posts the Actor scrapes.\n\nLinkedIn does not expose the full group roster, so 'members' here means everyone LinkedIn does surface for a group — typically the most-engaged 5–15% of the community. Each row has `linkedinUrl`, `fullName`, `headline`, and a back-link to the group, ready for profile enrichment.\n\nLeave it ON unless you only want group profiles or post content and want to skip member extraction entirely.", "default": true }, "extractCommenters": { "title": "Add commenters to the members list", "type": "boolean", "description": "When ON, for each post the Actor scrapes it also fetches the list of people who commented on that post, and adds them as member rows (memberSignal='commenter'). Each commenter is one billable row at the standard $0.005 per row. Typical: ~10 commenter rows per post, so a 50-post run adds ~500 commenter rows. Requires one extra upstream call per post (~+40% run time).", "default": false }, "extractReactors": { "title": "Add reactors to the members list", "type": "boolean", "description": "When ON, for each post the Actor scrapes it also fetches the list of people who reacted (liked / praised / etc.) to that post, and adds them as member rows (memberSignal='reactor'). Each reactor is one billable row at the standard $0.005 per row. Typical: ~10 reactor rows per post, so a 50-post run adds ~500 reactor rows. Requires one extra upstream call per post (~+40% run time).", "default": false }, "computeActivityMetrics": { "title": "Track group activity across runs", "type": "boolean", "description": "When ON, the Actor emits one extra row per scraped group (_type='group_activity') carrying: memberCount change since your last run, growth %, posts-per-day since the last snapshot, elapsed days between runs. Billed at the standard $0.005 per row. Uses no extra upstream calls; state is stored in this Task's key-value store, so each saved Task keeps its own history.\n\nFirst run captures a baseline (delta fields null). Second run and onward show real deltas — useful for weekly community-health monitoring via Apify Schedules.", "default": false }, "computeAdminOverlap": { "title": "Find admins who run multiple groups", "type": "boolean", "description": "When ON, at the end of the run the Actor emits one row per person who admins two or more of the groups scraped in this run (_type='admin_overlap'). Each row lists every group they admin, sorted by count descending. Uses zero extra upstream calls (works on admins already returned by the group-profile fetch). Only groups scraped in the SAME RUN can overlap — run in bulk to find hidden connectors.\n\nUseful for: finding influencers who anchor a niche, spotting content-farm operators running dozens of groups, mapping the human backbone of an industry vertical.", "default": false }, "computeGroupHealthScore": { "title": "Add health-score fields to each group", "type": "boolean", "description": "When ON, each group row gets an extra bundle of health-* fields describing its moderation setup, admin count, member count context, and (when post data is available) recent post activity + spam signals. Bundled inline into the group row — no new billable rows, no new upstream calls, no cost impact.\n\nFields added: healthMemberCount, healthAdminCount, healthIsModerated, healthIsPublic, healthGroupPlusActive, healthLabel.\n\nhealthLabel values — post-derived (when posts are scanned): 'very-active', 'active', 'quiet', 'dormant', 'high-spam'. Group-profile-only (Search & Get / Get Specific Groups modes): 'well-managed' (curated, moderated OR LinkedIn Group+), 'huge' (100k+ members), 'large' (10k-100k), 'mid-sized' (1k-10k), 'niche' (100-1k), 'micro' (<100), 'unknown' (no member count).\n\nUseful for filtering out spam groups, prioritizing well-managed communities, or scoring a search-and-get run before deep enrichment.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } } }