81 karma · joined March 3, 2011
nltk.org/book
I didn't expect wu-tang to be on the top since it would go across 11 different vocabs. I felt like the law of averages would basically play out.
I also had several suggestions to use shakespeare's sonnets rather than plays, which I should have done.
and yes, this is all just pinch of salt barbership discussion :)
http://www.mdaniels.com/vocab/scatter.png
love your other ideas – hopefully can do them later.
I used plain NLTK token analysis on rap genius lyrics. in terms of several more data slices...I agree that there should be more cuts of the data, but you must understand the amount of time that it took me to put this together.
mdaniels.com/vocab/scatter.png
so the average would change as your sample size grows.
35K was the threshold where things didn't get garbled (like the 100 word example that you mention).
The threshold is also impacted by who I include. If I went to 50K, I'd lose out on rappers like Drake.
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Point taken though.
I'm going to kill the greyscale hover. It doesn't do anything meaningful and had no idea it changed the text.