1. It doesn't count word frequencies, but sub-string frequencies. Moreover, if a sub-string appears more than once-per-title, then it is counted more than once.

1. It doesn't count word frequencies, but sub-string frequencies. Moreover, if a sub-string appears more than once-per-title, then it is counted more than once. I draw this conclusion by submitting "a,b,c". And from their paper [1]: our algorithm strips out dashes and catches any occurrence of the query in the title, for example, 'blow' catches 'blowing', 'blowjobs' This explains the results of these queries: "ada,erlang", "tea,beer". As an alternative they could have used a stemmer [2]. 2. The "slow,fast" and "love,hardcore" trends illustrate an interesting trend. Perhaps towards women or mainstream viewers. [1] http://sexualitics.org/wp-content/uploads/2014/01/PORNSTUDIES_preprint.pdf http://sexualitics.org/wp-content/uploads/2014/01/PORNSTUDIE... [2] http://nlp.stanford.edu/IR-book/html/htmledition/stemming-and-lemmatization-1.html http://nlp.stanford.edu/IR-book/html/htmledition/stemming-an...