Build a public discussion corpus for RAG
Khadin Akbar
Create a compact public LinkedIn post corpus around a focused business topic for grounded retrieval and citation-ready research.
Input
Output fields
Sign up on Apify or log in
The LinkedIn Post Search Scraper Actor is ready to run with the inputs already set for "Build a public discussion corpus for RAG". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Build a public discussion corpus for RAG" task
The LinkedIn Post Search Scraper Actor will start running based on the input automatically. You can also change all the input fields, like search query, date posted, and more, to match your specific use case.
Receive the "Build a public discussion corpus for RAG" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as position, post url, post id, and more.
Integrate into your workflow
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Build a public discussion corpus for RAG" task via API.
