Yesterday while pondering just that, I spoke with a friend and we decided to pull some data and make some graphs.
First order of business was to get a DB of posts, and it seemed like crawling was the only option.
But then luck strikes, and someone posts 6 months of HN data* !
Since what really interests me is the amount of traffic a post generates. I decided to get the average rating. With the assumption being:
- People read -> People vote -> High rank
I have ignored the relative placement on the main page, since a high placement during low-hours does not drive higher traffic, making the placement a poor indicator.
So, a bit of python and here it is:
The average Points and Comments for each post, based on its submission time (UTC).
The average Points and Comments for each post, based on its submission day-of-the-week.
With timing you can get your post almost 50% more.
These charts show the relative percentage of submission of front page articles based on time of submission (Hour(UTC) and Day-of-week):
* Please note that the DB used, only provides information on posts that made it to the main page. “Failed” submissions are not counted and might affect the results.