Science & Technology Review
|
2019, 37(21): 105-109
• Papers •
Artificial intelligence and big data as applied to Psychology
Full
LIU Xingyun1,2, LIU Xiaoqian1, XIANG Yuanyuan1,2, ZHU Tingshao1
Affiliations
1. Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China;
2. Department of Psychology University of Chinese Academy of Sciences, Beijing 100049, China
Published: 2019-11-13
doi: 10.3981/j.issn.1000-7857.2019.21.010
Outline
With the development of technology, artificial intelligence and big data have brought a new research strategy to psychology research. Compared with traditional methods, the combination of artificial intelligence and big data produces three advantages of ecological data:vertical tracking, time backtracking, high internal and external validity. This kind of interpersonal interaction based on Online Social Networking has profoundly affected or even changed people's psychological and behavioral characteristics. Meanwhile, ecological behavior data can be used, combined with other artificial intelligence technology, to establish a psychological index prediction model to achieve automatic identification of people's psychological indicators. This paper discusses the application of artificial intelligence and big data in psychological research and practice by taking personality prediction model, Proactive Suicide Prevention Online, and Qingdao prawn as examples. Finally, when using big data to analyze relevant psychological indicators, we must also pay attention to protecting user privacy and rational use of big data and artificial intelligence technology.
artificial intelligence (AI)
/
big data
/
psychology
/
ecological data
刘兴云, 刘晓倩, 向媛媛, 朱廷劭.
人工智能大数据之于心理学.
科技导报,
2019
, 37
(21)
: 105
-109
.
DOI: 10.3981/j.issn.1000-7857.2019.21.010
LIU Xingyun, LIU Xiaoqian, XIANG Yuanyuan, ZHU Tingshao.
Artificial intelligence and big data as applied to Psychology[J].
Science & Technology Review,
2019
, 37
(21)
: 105
-109
.
DOI: 10.3981/j.issn.1000-7857.2019.21.010
Year 2019 volume 37 Issue 21
PDF
573
146
Cite this Article
BibTeX
Article Info
doi: 10.3981/j.issn.1000-7857.2019.21.010
- Receive Date:2019-01-16
- Online Date:2019-11-15
- Published:2019-11-13