How to Scrape Instagram Comments at Scale — 1 Million Results and Counting

Instagram's official API is nearly useless if you need comment data at any real scale. Rate limits kick in almost immediately, OAuth setup is painful, and the data you actually get back is heavily filtered. For anyone doing sentiment analysis, influencer research, lead generation, or feeding an NLP pipeline — the official API just doesn't cut it. I've been running an Instagram comments scraper on Apify that has now processed over 1 million comments across hundreds of posts and reels. This article covers how it works, what the data looks like, and how to use it in your own Python pipeline. What People Actually Use This For Before getting into the technical side, here are the real use cases that show up most: Sentiment analysis — feeding large comment datasets into NLP models to understand audience reactions to a brand, product launch, or campaign. You need thousands of comments to get statistically meaningful results. The official API won't get you there. Influencer vetting — before sig