How I hacked Hacker News

dataphoric.com

7 pointsmcrowe3 comments

I looked at the data from 1.3 million Hacker News stories and found that when a story gets submitted makes a big difference (up to 172%). This article shows the analysis and results.

I used the official Hacker News API to get the stories using Python, and used R and ggplot2 to do the exploratory data analysis and plots.

I would love to see a meta-analysis of the 'when to post on HN' articles to see if a) there's consistency, and b) if the stories themselves have skewed subsequent conclusions (i.e.: will everyone now post at 7:45 on Sunday morning?)

Absolutely! The "success metric" will be different for different analyses, though, which would make that tough. The obvious choice is to look at the mean number of votes for stories submitted at different times. I looked at a binary condition instead: the fraction of stories which get more than N votes. This biases things less towards "super-star" stories which get tons of votes, and focuses on whether a story gets discovered at all.

There is a bunch of analysis I did behind the scenes to motivate this choose. I'll be posting the source code for my analysis, so it will be easy for anyone to critique and compare.

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