Substack Comments Sentiment Analysis
Collects 5 posts from the Astral Codex Ten archive along with up to 100 comments per post. Output has article text and metadata plus comment author, text, date and likes. Built as a dataset source for sentiment analysis, topic modeling and studying how readers respond to different kinds of posts.
Input
Output fields
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The Substack Scraper — Posts, Comments & Paraphrase with AI Actor is ready to run with the inputs already set for "Substack Comments Sentiment Analysis". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Substack Comments Sentiment Analysis" task
The Substack Scraper — Posts, Comments & Paraphrase with AI Actor will start running based on the input automatically. You can also change all the input fields, like start urls, max posts per start url, and more, to match your specific use case.
Receive the "Substack Comments 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 title, subtitle, authors, 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 "Substack Comments Sentiment Analysis" task via API.
