LinkedIn Comment Text Dataset for Sentiment Analysis

Created by

Chronometrica

Actor

LinkedIn Comments Scraper

Collect public LinkedIn comment text, author context, dates, and reaction counts as source rows for a separate sentiment model. No labels are created.

Try for free

LinkedIn Comments Scraperchronometrica/linkedin-comments-scraper

Input URL

Input Type

Post URL

Post URN

+9 fields

Input

Post URLs(required):https://www.linkedin.com/posts/timferriss_how-to-become-dramatically-more-productive-activity-7386884213343428608-wrF3

Maximum comments:100

Remove the result limit:false

Include author details:false

Output fields

Input URL

Input Type

Post URL

Post URN

Activity ID

UGC Post ID

Comment ID

Comment URL

Author

Author Headline

Comment

Reactions

Published At

How it works

Sign up on Apify or log in

The LinkedIn Comments Scraper Actor is ready to run with the inputs already set for "LinkedIn Comment Text Dataset for Sentiment Analysis". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "LinkedIn Comment Text Dataset for Sentiment Analysis" task

The LinkedIn Comments Scraper Actor will start running based on the input automatically. You can also change all the input fields, like post urls, maximum comments, and more, to match your specific use case.

Receive the "LinkedIn Comment Text Dataset for Sentiment Analysis" 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 input url, input type, post url, 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 "LinkedIn Comment Text Dataset for Sentiment Analysis" task via API.