Sentiment analysis

Sentiment analysis runs on text: reviews, forum threads, social replies, app store comments. Before any model sees it, that text has to come from somewhere, usually a page that wasn't built to be read by a script and often sits behind pagination, login walls, or anti-bot checks of its own.

01Where the text usually lives

• Review pages. Marketplace and app-store listings, paginated, often rendered client-side.
• Forums and communities. Threaded discussions where the useful signal is buried in replies.
• Social platforms. Public posts and comments, usually behind their own rate limits and protections.

02Getting from page to dataset

Fetch pulls the page itself, rendered and past whatever protection it has. For pages Extract already supports, Extract returns the review or post fields directly as structured data instead of raw text you'd parse yourself. For a large backlog, Batch runs the collection as one job instead of one request at a time.

03Frequently asked questions

Does Zenrows run the sentiment model itself?

No. Zenrows gets you the text; scoring it is up to whatever model or service you already use downstream.

Can this pull reviews from a specific marketplace?

Yes, see Amazon and the rest of the scrape library for real review-page examples.

What about pages behind a login?

Browser Sessions handles the parts of a site that need a signed-in session.