基于定序变量贝叶斯网结构学习的大五人格问卷分析
Analysis of the Big Five Personality Inventory by structural learning of Bayesian networks with ordinal variables
孙萌 1徐平峰1
作者信息
- 1. 长春工业大学 数学与统计学院,吉林 长春 130012
- 折叠
摘要
大五人格问卷是目前最权威的人格特质测评工具之一,通常采用定序数据的形式进行记录.针对大五人格问卷的贝叶斯网结构学习问题,选取 1 861 名东南亚人的大五人格问卷,应用 OPC算法进行分析,结果表明,同一特质的项目间相互关联更强.
Abstract
Currently,the Big Five Personality Inventory is one of the most authoritative personality trait assessment tools available,which is usually recorded in the form of ordinal data.For structure learning in Bayesian networks about the Big Five Personality Inventory,we select the Big Five Personality Inventory of 1 861 Southeast Asians and apply the OPC algorithm to analyze the questionnaire.The results show that the survey items are more correlated to each other within each trait.
关键词
贝叶斯网/定序变量/OPC/大五人格Key words
Bayesian networks/ordinal variable/OPC/Big Five Personality引用本文复制引用
基金项目
吉林省自然科学基金项目(20210101152JC)
出版年
2024
NETL
NSTL
万方数据