Three-Way Social Network Analysis: Triadic Measures at Three Levels

被引:0
|
作者
Chen, Yingxiao [1 ,2 ]
Yao, Yiyu [2 ]
Zhu, Ping [1 ,3 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China
[2] Univ Regina, Dept Comp Sci, Regina, SK S4S 0A2, Canada
[3] Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Math & Informat Networks, Beijing, Peoples R China
来源
ROUGH SETS, IJCRS 2023 | 2023年 / 14481卷
基金
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词
Three-way decision; Social network analysis; Triads; CONFLICT; ALLIANCE;
D O I
10.1007/978-3-031-50959-9_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Three-way decision, as thinking in threes, realizes the power of triads and has been successfully applied across diverse fields. Due to the important role played by triads, the basic ideas of triadic thinking appear in many studies on social network analysis. While measures based on the use of dyads (i.e., edges), the use of triads (i.e., triangles) has not received its due attention. This paper explores the value of triads in defining and interpreting measures in social network. We present an in-depth examination at the node, community, and network three levels. We propose a set of triadic measures at each level. These new measures contributes to a more comprehensive understanding of the structures and dynamics of social networks.
引用
收藏
页码:246 / 258
页数:13
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