Profiling a set of personality traits of a text’s author: A corpus-based approach

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Abstract

Authorship profiling, i.e. revealing information about an unknown author by analyzing their text, is a task of growing importance. Researchers are currently attempting to identify certain psychological characteristics of a text’s author (extraversion, openness, etc.). However, it is well-known that a lot of psychological traits mutually correlate making up what is known as a personality psychological profile. The aim of the study is to assess the probability of self-destructive behaviour of an individual as a set of particular traits via formal parameters of their texts. Here we have used corpus RusPersonality, which consists of Russian-language texts labeled with information on their authors. A set of correlations between scores on the Freiburg Personality Inventory scales that are known to be indicative of self-destructive behaviour and text variables has been calculated. A mathematical model which predicts the probability of self-destructive behaviour has been obtained.

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Litvinova, T., Zagorovskaya, O., Litvinova, O., & Seredin, P. (2016). Profiling a set of personality traits of a text’s author: A corpus-based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9811 LNCS, pp. 555–562). Springer Verlag. https://doi.org/10.1007/978-3-319-43958-7_67

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