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题名:
Predicting Active Users' Personality Based on Micro-Blogging Behaviors
作者: Li, Lin1,2; Li, Ang1,2; Hao, Bibo1,2; Guan, Zengda1,2; Zhu Tingshao(朱廷劭)1
文章类型: Article
刊名: PLOS ONE
ISSN号: 1932-6203
出版日期: 2014-01-22
卷号: 9, 期号:1, 页码:1-11
收录类别: SCI
英文摘要: 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.
语种: 英语
WOS记录号: WOS:000330283100019
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.psych.ac.cn/handle/311026/13443
Appears in Collections:社会与工程心理学研究室_期刊论文

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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

Recommended Citation:
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.
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