Tracking AI Coding Model Popularity via Hacker News Comments
By
yunusabd
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Summary
This article describes a system that tracks the popularity and sentiment of AI coding models based on Hacker News discussions. The pipeline collects the top 200 posts daily from HN, filters those about LLMs or coding, and analyzes sentiment from comments. It uses the OpenRouter catalog to detect which models are being discussed and scores sentiment to produce a daily ranking of coding model popularity.
Key quotes
· 3 pulledThe space of AI-assisted coding is evolving rapidly.
This is an attempt at staying up to date with the latest developments, by capturing popularity and user sentiment of coding models from Hacker News comments.
Each day, the pipeline gets the 200 most popular posts in a 24h window from the Hacker News API.
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