Every literary piece has a unique style composition. Addition of this style element to the text transforms the raw information into an artwork. In authorship attribution, this style is considered the author’s virtual fingerprint and is present in every text article composed by the author. There are several situations in everyday life where the author of a document needs to be identified, such as with the Federalist Papers where  the authors are unknown or the authorship is in dispute, or in forensic situations where the authenticity of a suicide note needs to be verified. Even in present-day cyberspace, the inherent anonymity is exploited to publish text articles of sensitive nature ranging from hate speech to fake news. Stylistic analysis can effectively assist in these situations by identifying the author of the text article.

Another ongoing thrust at FINS focuses on leveraging natural language processing, machine learning, and artificial intelligence to process, identify, and extract stylistic information from the text. This information is later utilized in matching an unknown document to its author and, by extension, even obtain heuristics on the author’s physical and psychological state.

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