Depressive Emotion Recognition Based on Behavioral Data | |
Yue Su1,2; Huijia Zheng1,3; Liu XQ(刘晓倩)1![]() ![]() | |
2019 | |
会议日期 | 2018.12 |
会议地点 | 墨西哥 |
关键词 | Diseases Learning systems Models Social networking |
英文摘要 |
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. |
会议录 | HCC 2018
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语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.psych.ac.cn/handle/311026/29137] ![]() |
专题 | 心理研究所_中国科学院行为科学重点实验室 |
作者单位 | 1.Institute of Psychology, Chinese Academy of Sciences 2.Department of Psychology, University of Chinese Academy of Sciences 3.St. Mark’s School, Southborough |
推荐引用方式 GB/T 7714 | Yue Su,Huijia Zheng,Liu XQ,et al. Depressive Emotion Recognition Based on Behavioral Data[C]. 见:. 墨西哥. 2018.12. |
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