The prev and curr values contain webpages, and n is the number of times users went from the prev webpage to curr webpage. So, each data row is a directed weighted edge, with the (prev, curr) pair describing the edge and the n being its weight. The dataset was cut off at n=10 (all edges with n <10 were dropped).
When I sum up the edge traffic n by prev webpages, to get outgoing traffic per webpage, I get the following log-log plot:
My question is about that little bump in the distribution at the top left. It occurs at outgoing traffic volume = 20, so my guess is that it's caused by cutting off the edge-level traffic n at 10. But if that's the case, why don't the frequency values immediately return to the power-law-like straight line followed by the rest of the data?
Here's a log(y) plot close-up of that bump in the distribution:
I'm guessing that smaller and smaller versions of these bumps repeat throughout these distributions at multiples of the n cutoff.
To summarize, my question is:
Why is the bump at the top left of these frequency distributions shaped like that? Why is it gradually going up instead of there being two disjoint downward-sloping straight lines?