| Texto completo | |
| Autor(es): |
dos Santos, Vitor Garcia
;
Paraboni, Ivandre
;
Ekstein, K
;
Matousek, V
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | TEXT, SPEECH, AND DIALOGUE, TSD 2017; v. 10415, p. 9-pg., 2017-01-01. |
| Resumo | |
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. (AU) | |
| Processo FAPESP: | 16/14223-0 - Tratamento Computacional da Personalidade Humana para Aplicações de Processamento de Língua Natural |
| Beneficiário: | Ivandre Paraboni |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |