This is a great idea! One that I've played around with, such as using word clouds on various wikileak emails. A different approach I've been attempting is comparing writing samples, based on a DefCon presentation I came across awhile back. A separate project has been to automate a process/script that does the following:   Sample the current news as being published by a list of websites a) Include twitter/facebook/etc sources for trends b) Provide a method of providing a word/phrase as input   Take the sample/word phrase and run it through all news sites, providing a list of them that have used it (look for natural vs created trends, i.e. fake and planned news)   Take the same phrase/word and input it into a search/query that gophers/crawls through all of the wikileak emails, and other provided 'databases' of such leaked files/emails/documents, etc.   Create a list of emails/documents which mentioned the word/phrase that we sampled from (1) and include in that list, if applicable, the from/to/people involved with those emails/documents, including those mentioned within them.    Any criticism would be appreciated. Going to attempt it first with Python. Any suggestions, I'd welcome them!