BLN-Gram-TF-ITF as a new Feature for Authorship Identification

Authorship attribution is the methodology of determining the specific author of a text originating from a corpus of texts created by one or multiple authors. By analyzing and measuring specific textual features, one can construct a profile to identify a specific author. This type of identification of authors via their writing style is one of the most engaging problems for researchers of stylometry. As it relates to authorship identification, the primary goal of our research is to identify an author of text through analysis of stylistic traits. We present a new feature that demonstrates initial success in identifying correct authors of text through the analysis of those authors’ text corpus. Byte Level N-Gram Term Frequency Inverse Token Frequency (BLN-Gram-TF-ITF) is successfully implemented on a set of text corpus and shows promising outcomes.

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