Statistically Improbable Phrase

A statistically improbable phrase (SIP) is a phrase or set of words that occurs more frequently in a document (or collection of documents) than in some larger corpus.[1][2][3] uses this concept in determining keywords for a given book or chapter, since keywords of a book or chapter are likely to appear disproportionately within that section.[4][5] Christian Rudder has also used this concept with data from online dating profiles and Twitter posts to determine the phrases most characteristic of a given race or gender in his book Dataclysm

Using NLTK

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