Abstract
This paper investigates which Big Five personality traits are best predicted by different text genres, and how much text is actually needed for the task. To this end, we compare the use of ‘free’ Facebook text with controlled text elicited from visual stimuli in descriptive and referential tasks. Preliminary results suggest that certain text genres may be more revealing of personality traits than others, and that some traits are recognisable even from short pieces of text. These insights may aid the future design of more accurate models of personality based on highly focused tasks for both language production and interpretation.
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CITATION STYLE
Dos Santos, V. G., Paraboni, I., & Silva, B. B. C. (2017). Big five personality recognition from multiple text genres. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10415 LNAI, pp. 29–37). Springer Verlag. https://doi.org/10.1007/978-3-319-64206-2_4
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