Analyzing Hacker News Users’ Join Dates, Karma, and Profiles

Linear fits? Why? <i>Why</i>?<p>Karma is a function of time since joining, participation, and quality of contributions. And it starts at 1. 'Participation' can be determined by looking at contributions per length of time. Quality is average score of each submission -- separating it from participation is a useful way to extend this to a more complicated model taking into account the fact that people stop using HN. So the line of best fit should be something closer to 1 + t * q * p, or the sum of 1 + (t0 * q * p0) + .... (t<i>n</i> * q * p<i>n</i>) to describe folks who are off-and-on contributors.

Could you post "General Composition of the Dataset" with a logarithmic vertical scale please? Should help compensate for the outliers so we can see more detail at the bottom of the graph.

"I didn’t really expect to find a whole lot of interesting things, and found what I expected."<p>Which is a great way to conduct research! Nice work.<p>This reminded me of my senior project in number theory, when I manipulated a large data set, wondering what I'd find. Eventually, I found quite a bit.<p>Also reminded me of this quote by Wernher von Braun:<p>"Basic research is what I am doing when I don't know what I'm doing."

You may want to take into account differences in file timestamps because the data was collated over many days.

The interesting thing about karma.. I find that I can't/I get tired of posting insightful comments day after day..and take breaks and lurk..edw519 I don't know how you do it. I probably won't make the "leaders" (but I don't think its important)

Nice work. I love manipulating large data sets :)<p>Which program did you use to produce the plots?

Scatterplots are too dense!

Just curios, how does the karma point work?