Linkedin Post Search Scraper ($1.50/1000 results)
Pricing
from $1.50 / 1,000 results
🔎 Search LinkedIn posts by keyword, then choose a result limit or collect every available result.
You can access the Linkedin Post Search Scraper ($1.50/1000 results) programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
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Examples: `generative AI`, `\"product launch\"`, or `\"artificial intelligence\" OR \"machine learning\"`. Use uppercase `AND` to require both terms (`AI AND marketing`) and `NOT` to exclude a term (`hiring NOT internship`). Enter straight double quotes directly in this field; escape quotes only when writing JSON input. The Actor fixes curly quotes and removes redundant outer parentheses while preserving meaningful groups. Keep complex queries short. Invalid syntax stops the run gracefully with an explanation. See the README for more examples and search tips." }, "contentType": { "title": "🎞️ Content type", "enum": [ "videos", "photos", "jobs", "liveVideos", "documents", "collaborativeArticles" ], "type": "string", "description": "Only return this type of post." }, "sort": { "title": "↕️ Sort results", "enum": [ "relevance", "date_posted" ], "type": "string", "description": "Order returned by the search API.", "default": "relevance" }, "maxPosts": { "title": "🔢 Maximum posts", "minimum": 50, "type": "integer", "description": "Maximum number of raw posts to save. Ignored when Parse all posts is enabled.", "default": 100 }, "parseAll": { "title": "Parse all posts", "type": "boolean", "description": "Continue until all reported search results are fetched or the API returns an empty page.", "default": false }, "authorTitle": { "title": "💼 Author title", "type": "string", "description": "Filter by the author's professional title." }, "datePosted": { "title": "📅 Date posted", "enum": [ "past-24h", "past-week", "past-month" ], "type": "string", "description": "Only posts from the selected time period." }, "fromOrg": { "title": "🏢 Posted by organization", "type": "string", "description": "Company name to filter posts published by an organization. The first matching LinkedIn company is used." }, "authorCompany": { "title": "🏢 Author company", "type": "string", "description": "Company name to filter authors by employer. The first matching LinkedIn company is used." }, "mentioningOrg": { "title": "🏷️ Mentioned organization", "type": "string", "description": "Company name that must be mentioned in a post. The first matching LinkedIn company is used." }, "authorIndustry": { "title": "🏭 Author industry", "type": "string", "description": "Industry name or keyword used to filter post authors. 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It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Linkedin Post Search Scraper ($1.50/1000 results) from the options below:
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