Blogs and Twitter Feeds: A Stylometric Environmental Impact Study

Stylometry is the study of determining the author of a document based on the linguistic features contained in the document. Previous work in this area has yielded impressive results, but assumes that the training and testing documents are similar key attributes, namely the domain and setting in which they are written. This paper focuses on the scenario where this assumption cannot be made. We determine that standard methods in stylometry do not perform well when the training and suspect documents differ in this way. For example, when working exclusively with blogs we obtain an average accuracy of 93.30% and with Twitter feeds we obtain an average accuracy of over 98.99%. However, when we apply the same method to try to identify a twitter feed via a blog’s writing, accuracy falls drastically. We provide a method to improve this cross-domain accuracy to 88.89%. Being able to identify authors across domains facilitates linking identities across the Internet, making this a key privacy concern.

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