Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research

doi:10.1111/aphw.12590

PSYCH OpenIR

	Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research
	Han, Nuo 1,2; Wen, Yeye 3; Wang, Bowen 4; Huang, Feng 5,6; Liu, Xiaoqian 5; Li, Linyan 2,7; Zhu, Tingshao 5,6
通讯作者	Li, Linyan(linyanli@cityu.edu.hk) ; Zhu, Tingshao(tszhu@psych.ac.cn)
摘要	Demystifying machine learning (ML) approaches through the synergy of psychology and artificial intelligence can achieve a balance between predictive and explanatory power in model development while enhancing rigor in validation and reporting standards. Accordingly, this study aimed to bridge this research gap by developing a subjective well-being (SWB) prediction model on Weibo, serving as a psychological assessment instrument and explaining the model construction based on psychological knowledge. The model establishment involved the collection of SWB scores and posts from 1,427 valid Weibo users. Multiple machine learning algorithms were employed to train the model and fine-tune its parameters. The optimal model was selected by comparing its criterion validity and split-half reliability performance. Furthermore, SHAP values were calculated to rank the importance of features, which were then used for model interpretation. The criterion validity for the three dimensions of SWB ranged from 0.50 to 0.52 (P < 0.001), and the split-half reliability ranged from 0.94 to 0.96 (P < 0.001). The identified relevant features were related to four main aspects: cultural values, emotions, morality, and time and space. This study expands the application scope of SWB-related psychological theories from a data-driven perspective and provides a theoretical reference for further well-being prediction.
关键词	domain knowledge life satisfaction machine learning social media subjective well-being Weibo
	2024-08-21
语种	英语
DOI	10.1111/aphw.12590
发表期刊	APPLIED PSYCHOLOGY-HEALTH AND WELL BEING
ISSN	1758-0846
页码	20
收录类别	SCI
出版者	WILEY
WOS关键词	AFFECT SCHEDULE PANAS ; SOCIAL MEDIA ; PERSONALITY ; FACEBOOK ; TWITTER ; HAPPINESS ; VALIDITY ; REFLECT ; CULTURE ; EVENTS
WOS研究方向	Psychology
WOS类目	Psychology, Applied
WOS记录号	WOS:001295402200001
引用统计
文献类型	期刊论文
条目标识符	https://ir.psych.ac.cn/handle/311026/49105
通讯作者	Li, Linyan; Zhu, Tingshao
作者单位	1.Beijing Normal Univ, Fac Arts & Sci, Dept Psychol, Zhuhai, Peoples R China 2.City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China 3.Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing, Peoples R China 4.Helmholtz Ctr Potsdam, GFZ German Res Ctr Geosci, Potsdam, Germany 5.Chinese Acad Sci, Inst Psychol, CAS Key Lab Behav Sci, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China 7.City Univ Hong Kong, Jockey Club Coll Vet Med & Life Sci, Dept Infect Dis & Publ Hlth, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Han, Nuo,Wen, Yeye,Wang, Bowen,et al. Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research[J]. APPLIED PSYCHOLOGY-HEALTH AND WELL BEING,2024:20.
APA	Han, Nuo.,Wen, Yeye.,Wang, Bowen.,Huang, Feng.,Liu, Xiaoqian.,...&Zhu, Tingshao.(2024).Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research.APPLIED PSYCHOLOGY-HEALTH AND WELL BEING,20.
MLA	Han, Nuo,et al."Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research".APPLIED PSYCHOLOGY-HEALTH AND WELL BEING (2024):20.