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Enabling Codex to Analyze Two Decades of Hacker News Data

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Why This Matters

This development showcases how advanced AI tools like Codex, combined with Modolap, can efficiently analyze large-scale datasets such as two decades of Hacker News data. It highlights the potential for automating complex data queries and trend analysis, empowering both researchers and industry professionals to derive insights quickly. Such capabilities are poised to transform data-driven decision-making across the tech industry and enhance consumer understanding of technology trends.

Key Takeaways

The entirety of Hacker News, stored in parquet files, is approximately 10GB in size. I was interested in analyzing the dataset and, in the fashion of the contemporary zeitgeist, in doing so with Codex. With Modolap, Codex can analyze it well.

After simply adding the skill with npx , the first topic of interest was mention history: whether mentions of Rust superseded those of Go, and MySQL versus Postgres. Simply running

codex "With Modolap, Write a query to analyze historical keyword-based topic mentions over hacker news's history (Dataset's homepage: https://huggingface.co/datasets/open-index/hacker-news/tree/main). Initially, of Rust vs Go."

and some minimal back-and-forth yielded an adequate script using Modolap.

Rust vs Golang

Codex vs Claude Code

Postgres vs MySQL

An additional hypothesis is whether the average comment got shorter. From an initial look, it seems as if there does exist a gradual decline in length.

P50 & Average Comment Length (Chars)