方法对比

	Structural Balance Theory	Dyadic Analysis	社会网络分析
领域	Sociology	Sociology	网络分析
方法族	Process / pipeline	Regression model	Machine learning
起源年份	1946 (Heider); 1956 (Cartwright & Harary)	1981	1934 (sociometry); 1994 (modern formalization)
提出者	Fritz Heider; formalized by Dorwin Cartwright & Frank Harary	Holland & Leinhardt (p1); Kenny (Social Relations Model)	Moreno, J.L.; formalized by Wasserman & Faust
类型	Theory and graph-theoretic test for tension in signed relationships	Analysis of the dyad as the unit, decomposing relational effects	Structural/relational analysis framework
开创性文献	Cartwright, D., & Harary, F. (1956). Structural balance: a generalization of Heider's theory. Psychological Review, 63(5), 277–293.	Holland, P. W., & Leinhardt, S. (1981). An exponential family of probability distributions for directed graphs. Journal of the American Statistical Association, 76(373), 33–50.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
别名	balance theory, Heider balance, signed network balance, structural balance analysis	dyad analysis, dyadic data analysis, social relations model, dyad census	SNA, network analysis, sociometric analysis, relational analysis
相关	5	4	5
摘要	Structural balance theory analyzes networks whose ties carry a sign — positive for liking, alliance, or trust, negative for hostility or distrust — and asks which configurations are psychologically and socially stable. Originating in Fritz Heider's cognitive balance principle and given a graph-theoretic form by Dorwin Cartwright and Frank Harary in 1956, it predicts that signed networks evolve toward states free of the tension produced by inconsistent triads such as 'the friend of my enemy'.	Dyadic analysis treats the dyad — the pair of actors and the relation between them — as the unit of analysis, separating the relational outcome into what each actor brings to all their relationships and what is unique to the specific pair. It spans the descriptive dyad census of network analysis and statistical frameworks such as Holland and Leinhardt's p1 model and Kenny's Social Relations Model, all of which respect the structural non-independence inherent in relational data.	Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.