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

文献类型：期刊论文

作者Han, Nuo1,2; Wen, Yeye3; Wang, Bowen4; Huang, Feng5,6; Liu, Xiaoqian5; Li, Linyan2,7; Zhu, Tingshao5,6
刊名APPLIED PSYCHOLOGY-HEALTH AND WELL BEING
出版日期2024-08-21
页码20
关键词domain knowledge life satisfaction machine learning social media subjective well-being Weibo
ISSN号1758-0846
DOI10.1111/aphw.12590
通讯作者Li, Linyan(linyanli@cityu.edu.hk) ; Zhu, Tingshao(tszhu@psych.ac.cn)
英文摘要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.
收录类别SCI
WOS关键词AFFECT SCHEDULE PANAS ; SOCIAL MEDIA ; PERSONALITY ; FACEBOOK ; TWITTER ; HAPPINESS ; VALIDITY ; REFLECT ; CULTURE ; EVENTS
WOS研究方向Psychology
语种英语
WOS记录号WOS:001295402200001
出版者WILEY
源URL[http://ir.psych.ac.cn/handle/311026/48768]  
专题心理研究所_中国科学院行为科学重点实验室
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.

入库方式： OAI收割

来源：心理研究所

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