We study techniques for identifying an anonymous author via linguistic stylometry, i.e., comparing the writing style against a corpus of texts of known authorship. We experimentally demonstrate the effectiveness of our techniques with as many as 100,000 candidate authors. [...] In over 20% of cases, our classiﬁers can correctly identify an anonymous author given a corpus of texts from 100,000 authors; in about 35% of cases the correct author is one of the top 20 guesses.On the Feasibility of Internet-Scale Author Identiﬁcation[pdf] is a draft of a paper for the IEEE Symposium on Security and Privacy.
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