A recent blog post by Newbe36524 introduces a practical method for mining social network data to inform AI research and product decisions. The approach leverages the last30days tool to aggregate signals from platforms like Reddit, X, YouTube comments, TikTok, Hacker News, and Polymarket. The author argues that while individual posts or votes may seem like noise, collectively they form a valuable snapshot of public opinion. This technique is particularly useful for indie hackers and product teams who need real-time market feedback without expensive surveys. The post provides a framework for filtering, analyzing, and interpreting these signals to identify trends, user pain points, and feature opportunities. For developers building AI products, this method offers a low-cost, data-driven way to validate hypotheses and stay ahead of market shifts. The signal is timely as more teams seek authentic user data beyond traditional analytics.
Learn how to use last30days to aggregate social media signals for AI research and product validation.