PSYCH OpenIR  > 中国科学院行为科学重点实验室
Depressive Emotion Recognition Based on Behavioral Data
Yue Su1,2; Huijia Zheng1,3; Liu XQ(刘晓倩)1; Tingshao Zhu1
First AuthorYue Su
2019
Conference NameHuman-Centered Computing (HCC 2018)
Correspondent Emailtszhu@psych.ac.cn
Source PublicationHCC 2018
Conference Date2018.12
Conference Place墨西哥
Abstract

 

With the increase of pressure in people’s lives, depression has become one of the most common mental illness worldwide. The wide use of social media provides a new platform for depression recognition based on people’s behavioral data. This study utilizes the linguistical psychological characteristics of Weibo users to predict users’ depression level. The model adopts the Gaussian process regression algorithm, sets the PUK kernel as the kernel function, applies the forward-backward search method to select feature, and uses five-fold cross-validation to evaluate performance of the model. This study finally established a prediction model with a correlation coefficient of 0.5189, which achieved a medium correlation in the psychological definition, and provided a more accurate method for the auxiliary diagnosis of depression.

KeywordDiseases Learning systems Models Social networking
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.psych.ac.cn/handle/311026/29137
Collection中国科学院行为科学重点实验室
Affiliation1.Institute of Psychology, Chinese Academy of Sciences
2.Department of Psychology, University of Chinese Academy of Sciences
3.St. Mark’s School, Southborough
First Author AffilicationInstitute of Psychology, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Yue Su,Huijia Zheng,Liu XQ,et al. Depressive Emotion Recognition Based on Behavioral Data[C],2019.
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