Big Five Personality Recognition from Multiple Text Genres

被引：9

作者：

dos Santos, Vitor Garcia ^{[1
]}

Paraboni, Ivandre ^{[1
]}

机构：

[1] Univ Sao Paulo, Sch Arts Sci & Humanities, Sao Paulo, Brazil

来源：

TEXT, SPEECH, AND DIALOGUE, TSD 2017 | 2017年 / 10415卷

基金：

巴西圣保罗研究基金会;

关键词：

Big Five; Personality recognition;

D O I：

10.1007/978-3-319-64206-2_4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：29 / 37

页数：9

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