Quote:
Originally Posted by pelagius
I guess I am still unsure of what you are looking for, Solon (I promise I am not trying to give you a hard time about this. I hope it doesn't come across that way. I am honestly never quite sure what level of detail want when they ask statistical questions). Did you want me to explain the methodology used in the paper? If you want then I can do that (I would be surprised if you really want me to). For example, one of his core measures is the Sichel Distribution which measures the probability that a word (he only uses nouns) appear X times in a N word sample (N=1000 in the paper). The distribution is a two parameter distribution: alpha and theta (they jointly describe the shape of the distribution the way mean and standard deviation do for the normal distribution). The author doesn't specify but it makes most sense to estimate the distribution using Maximum likelihood. You then can compare the different writing samples by testing if the alpha's and theta's are different across the writing samples.
He then combines this measure with 4 other similar measures and then explores commonality using two different approaches: cluster analysis and principal component analysis.
Are you asking for a comment on whether this approach is subjective?
There some truth to that charge. The stylometrician has a fair amount of degrees of freedom in terms of the design of the test.
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No, you're not giving me a hard time, and thanks for all the details you provide. I have nothing other than passing curiosity, and wondered if anyone was familiar with this type of endeavor and what he/she thought of it. Has stylometry been accepted in other fields, or is this just a statistical game? I'm not looking for hardcore answers, just curious about the size of the iceberg beneath this tip.