I measured the half-life of 41,301 Show HN launches. It's 7 hours
I scraped every Show HN from the last 12 months (41,301 posts) plus the full comment tree of every launch with 10+ comments, ~100k comment timestamps, all from the Algolia HN API. The median launch gets 2 points and 0 comments. For launches that do get traction, half the comments they'll ever get arrive within 7.2 hours and 90% within 26, and the top decile decays on the same clock as everyone else. Vote timestamps aren't public, so comment timing is the attention proxy; caveats are in the post. Everything reproduces from the repo with one command…
In plain words
This project analyzes 41,301 Show HN posts from the past year, examining comment timing patterns to understand audience engagement lifecycles. Using Hacker News API data, the researcher found that successful launches receive half their total comments within 7.2 hours and 90% within 26 hours, regardless of initial success level. The analysis is fully reproducible through an open-source repository, making methodology transparent and verifiable for other developers studying community dynamics and content visibility.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I scraped every Show HN from the last 12 months (41,301 posts) plus the full comment tree of every launch with 10+ comments, ~100k comment timestamps, all from the Algolia HN API. The median launch gets 2 points and 0 comments. For launches that do get traction, half the comments they'll ever get arrive within 7.2 hours and 90% within 26, and the top decile decays on the same clock as everyone else. Vote timestamps aren't public, so comment timing is the attention proxy; caveats are in the post. Everything reproduces from the repo with one command (https://github.com/jonnonz1/hn-attention-cliff), and every number in the post maps to a named function. Keen to hear where the methodology falls short
Does the same job
all alternatives →- 2G22 GB of Hacker News in SQLiteDec 2025 · hackerbook.dosaygo.com · ▲730
Community, All the HN belong to you. This is an archive of hacker news that fits in your browser. When I made HN Made of Primes I realized I could probably do this offline sqlite/wasm thing with the whole GBs of archive. The whole dataset. So I tried it, and this is it. Have Hacker News on your device. Go to this repo (https://github.com/DOSAYGO-STUDIO/HackerBook): you can download it. Big Query -> ETL -> npx serve docs - that's it. 20 years of HN arguments and beauty, can be yours forever. So they'll never die. Ever. It's the unkillable static archive of HN and it's…
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I love HN but always felt the search with algolia is okay but does have some limitations. Since I work at Vectara I decided to try and create a better search for HN. It's based on data from roughly the last 6 months of HN stories and comments. Would love to hear feedback and how useful this is relative to the existing search.
Posts grew 6x since ChatGPT, but success rate remained relatively flat25d ago · orangecrumbs.com · ▲11Show HN submissions peaked at 6.3x their ChatGPT-launch level, while the number of successful submissions remained relatively flat.
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- ATAnalyzing top HN posts with language models2022 · ▲117
Hi HN, I spent a few weeks looking at the top HN posts of all time. This included exploration, clustering, creating visualizations, and zooming in on what (to me personally) seems like some of the best discussions on here. Three things in this post: 1- The interesting groups of HN posts 2- The interactive visualizations that you can explore in your browser 3- The data from this exploration -- this includes CSV of the titles as well as the text embeddings of 3,000 Ask HN articles. Blog post about this whole process here: [1] ============ 1- The interesting groups of HN posts From the…
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