Spawning an idea... process followers the same exact way... via classification! Same rules, +/- one standard deviation around the 10% expectancy... classify via Hot Cold and Neutral the same way... 

Then...

Record the intersections of the resultant neutral sets ! 

Not as safe of a reduction, but it might help identify a correlation between the raw frequency and follower frequency. Would need to increase the follower set to 1,500 because holding the followers to their theoretical 10% expectancy will make 150 raw draws perfectly mesh with 1,500 follower draws... apples to apples.

If there is no direct correlation in frequency, the data should show that also. Then I will know... one way or the other.

This will take some time to implement, so there may be some "radio silence" after the test is done. The follower set may not be as uniform... but it should be, in theory anyway.