hnr – a terminal Hacker News reader vibe-coded in Rust
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NPS-scored sentiment graphs for HN threads, but Remove.bg and Sentiment140 already do this.
Hacker News users, market researchers, job hunters evaluating company discussions
Sentiment140 · MonkeyLearn · AWS Comprehend
I’ve found digging deep on HN to be useful include when my spouse and I were deciding whether we should take job offers from companies that have been discussed, when doing (very biased) market research on a feature or product, and when learning about new technology
During my most recent comment deep dive, I built a tool to analyze and visualize the sentiment of each comment as a graph and make it pleasant to navigate. I also extracted keyword phrases so they could be counted and compared by sentiment. I used net promoter score (NPS) as a framework for sentiment aggregation
I decided to productize and share my work. HN Sentiment Tool (HST) is a static page built with SvelteKit where you paste a HN URL, paste an OpenRouter API key (you can audit the code or clone and run locally), choose a model, then analyze and visualize the sentiment comment by comment and across the entire post
The tool loads complete with a polarizing thread about Peter Steinberger joining OpenAI to give you an idea of how it works
I hope you find HST a fun and useful research tool. Let me know if you have any questions or suggestions
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Clean HN reader, but Relay and Sync already dominate Android HN clients.
Surfaces comment insights instead of articles when HN newsletters already exist.
Handy, focused slice of HN history — the UI gives immediate controls for sorting by points, comments, backlinks and even snapshotting, so you can eyeball what topics dominated each year. The listing is readable and the filters in the header imply some non-trivial backlink/discussion aggregation behind the scenes. I want clearer methodology, export options and time-series views before this becomes a must-bookmark tool.
Polished HN client for macOS, but web version and third-party clients already exist.
164 personas commenting on news, but the novelty wears off after one thread.