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Predicting Depression of Social Media User on Different Observation Windows
Hu, Q (Hu, Quan)1; Li, A (Li, Ang)2,3; Heng, F (Heng, Fei)4; Li, JP (Li, Jianpeng)4; Zhu, TS (Zhu, Tingshao)5
第一作者Hu, Q (Hu, Quan)
2015
会议名称IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
会议录名称IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
卷号1
期号不详
页码361-364
会议日期DEC 06-09, 2015
会议地点Singapore, SINGAPORE
摘要

Depression has become a public health concern around the world. Traditional methods for detecting depression rely on self-report techniques, which suffer from inefficient data collection and processing. This paper built both classification and regression models based on linguistic and behavioral features acquired from 10,102 social media users, and compared classification and prediction accuracy respectively among models built on different observation windows. Results showed that users' depression can be predicted via social media. The best result appears when we make prediction in advance for half a month with a 2-month length of observation time.

关键词Machine Learning Depression Microblogging Behavior Classification Prediction
DOI10.1109/WI-IAT.2015.166
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.psych.ac.cn/handle/311026/26555
专题社会与工程心理学研究室
作者单位1.Henan Univ, Inst Psychol, Chinese Acad Sci, Sch Comp & Informat Engn, Kaifeng, Peoples R China
2.Beijing Forestry Univ, Dept Psychol, Beijing, Peoples R China
3.Univ New South Wales, Black Dog Inst, Sydney, NSW 2052, Australia
4.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China
5.Chinese Acad Sci, Inst Comp Technol, Inst Psychol, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Hu, Q ,Li, A ,Heng, F ,et al. Predicting Depression of Social Media User on Different Observation Windows[C],2015:361-364.
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