Predicting Big Five Personality Traits of Microblog Users

Personality can be defined as a set of characteristics which makes a person unique. The study of personality is of central importance in psychology. Conventional personality assessment is performed by self-report inventory, which costs much manual efforts and cannot be done in real time. To solve th...

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Vydáno v:2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) Ročník 1; s. 501 - 508
Hlavní autoři: Shuotian Bai, Bibo Hao, Ang Li, Sha Yuan, Rui Gao, Tingshao Zhu
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2013
Témata:
Arrays
Big-Five personality
Correlation
Feature extraction
Linear regression
Noise measurement
personality
predic-tion
Predictive models
regression
Sina microblogs
Training
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Shrnutí:Personality can be defined as a set of characteristics which makes a person unique. The study of personality is of central importance in psychology. Conventional personality assessment is performed by self-report inventory, which costs much manual efforts and cannot be done in real time. To solve these problems, this research aims to measure the Big-Five personality from the usages of Sina Microblog objectively. By conducting a user study with 444 users, this paper proposes multi-task regression and incremental regression algorithms to predict the Big-Five personality from online behaviors. The results indicate that personality can be predicted with a high accuracy through online Microblog usage.
DOI:10.1109/WI-IAT.2013.70