voytek

According to Forbes' managing editor, their bloggers are paid a flat rate for a minimum number of posts and comments, but that yes, they are given incentives for monthly uniques and repeat traffic:

http://www.quora.com/Do-Forbes-bloggers-get-paid-or-are-they...

Some of it is: http://www.infochimps.com/datasets/uber-anonymized-gps-logs

25000 trips, anyway.

Oops, forgot to respond to this! You're welcome. Don't get me wrong, Cracked can be very good for spurring on interest as well, but sometimes it's good to have references. :)

It's exactly this discrepancy that I find so fascinating! It's what I spent my PhD on :)

I believe that the two major players here are plasticity and connectivity. If you lose a critical hub in the network, you're going to be much worse off than if you lose a loosely connected, plastic region.

That's the point of these two papers: http://www.ncbi.nlm.nih.gov/pubmed/20921401 <- free open access http://www.ncbi.nlm.nih.gov/pubmed/21040843 <- lame closed

Heh. Damn right it's linkbait. My entire scientific outreach efforts are linkbait. Dude, I talk about zombie brains to the public.

Do you know how hard it is to get the most of the non-science public to care about science? If I can get people reading about the stuff that I find cool and mindblowing, and that makes them want to learn more on their own, then hell yeah I'm going for the linkbait title.

I'm not making money off this site. I don't give a damn about my SEO or bouncerate or whatever. I write this in my free time because I love the brain. And hopefully some of that accidentally rubs off on people.

Man you folks are more harsh than peer-reviewers! :)

And here I was thinking to myself when I wrote the post, "people don't want to be drowning in data; they want something interesting based on the data". Dang. I was wrong!

On its own, that chart would be shady, you're right. For the purposes of the data I was trying to show (that weekend and weekday rides are quite similar), that was the best way to plot the data.

Of course if I take a linear function, and plot its integral, it will be exponential. By definition. I recognize that.

But that's why I also plotted the weekly averages farther down. You can see the non-linear growth very clearly in that chart. In fact, if I log-transform the average rides per week, the plot is quite linear (as would be expected for exponential growth). r(ln(rides)) = 0.83

Your comment about the slope since last November being "pretty linear" is misleading, too, though!

If you take an exponential function, and arbitrarily select any sub-segment of it, that sub-segment will always have a better linear fit than the linear fit for the whole function.

So by definition, mathematically, you're right. Our growth since November has been more linear than the overall history of our growth. Just as the first three months were also more linear. Or during any other arbitrary time period.

So I happily submit my revised manuscript for your reconsideration. I hope I have adequately and thoroughly addressed all of the reviewers concerns. Thank you.

Touché. I was definitely being technically unclear. My usage there was meant to indicate that the effect of the holidays on ridership was wildly higher than we had expected. Now that we've had a few holidays, we can begin to build that crazy surge into our models.

So yes, certainly the holidays themselves are predictable, but their effect on rides was not.

But now is. :)