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Predicting Active Users' Personality Based on Micro-Blogging Behaviors
Li, Lin1,2; Li, Ang1,2; Hao, Bibo1,2; Guan, Zengda1,2; Zhu, Tingshao1
摘要Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 845 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors.
2014-01-22
语种英语
发表期刊PLOS ONE
ISSN1932-6203
卷号9期号:1页码:1-11
期刊论文类型Article
收录类别SCI
WOS记录号WOS:000330283100019
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被引频次:39[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/13443
专题社会与工程心理学研究室
作者单位1.Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control, Beijing, Peoples R China
第一作者单位中国科学院心理研究所
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GB/T 7714
Li, Lin,Li, Ang,Hao, Bibo,et al. Predicting Active Users' Personality Based on Micro-Blogging Behaviors[J]. PLOS ONE,2014,9(1):1-11.
APA Li, Lin,Li, Ang,Hao, Bibo,Guan, Zengda,&Zhu, Tingshao.(2014).Predicting Active Users' Personality Based on Micro-Blogging Behaviors.PLOS ONE,9(1),1-11.
MLA Li, Lin,et al."Predicting Active Users' Personality Based on Micro-Blogging Behaviors".PLOS ONE 9.1(2014):1-11.
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