Graph Models and Networks in Psychology

被引:1
作者
Ruiz-Ruano Garcia, Ana Maria [1 ]
Lopez Puga, Jorge [2 ]
机构
[1] Univ Granada, Fac Educ, Dept Psicol Evolut & Educ, Campus Cartuja, Granada, Spain
[2] UCAM Univ Catolica Murcia, Fac Ciencias Salud, Campus Jeronimos, Murcia, Spain
来源
REVISTA DE HISTORIA DE LA PSICOLOGIA | 2020年 / 41卷 / 04期
关键词
graph models; Bayesian networks; network analysis; psychology; MARKOV-MODELS; COMORBIDITY; MECHANISMS; CAUSALITY; JUDGMENT; CHILDREN;
D O I
10.5093/rhp2020a18
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Network analysis is not a new methodology in psychology. However, network analysis-based methodologies are more and more common nowadays. Here we provide a historical review of two areas in which network analysis has been critical for psychology: causal cognition and psychopathology. We briefly review key points in the history of philosophy contributing to progresses in the scientific research about causal cognition. We show how those progresses evolved to considering Bayes networks as normative models to understand causal cognition. We also provide some notes about how network analysis allows to understand mental disorders. Finally, some future paths development regarding the usage of graphs models are suggested as well as some problems to avoid in the close future into this line of research.
引用
收藏
页码:24 / 33
页数:10
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