방법 비교

	Dyadic Analysis	Homophily Analysis	사회 연결망 분석
분야	Sociology	Sociology	네트워크 분석
계열	Regression model	Process / pipeline	Machine learning
기원 연도	1981	1954 (concept); 2001 (synthesis)	1934 (sociometry); 1994 (modern formalization)
창시자	Holland & Leinhardt (p1); Kenny (Social Relations Model)	Lazarsfeld & Merton (concept); McPherson, Smith-Lovin & Cook (synthesis)	Moreno, J.L.; formalized by Wasserman & Faust
유형	Analysis of the dyad as the unit, decomposing relational effects	Measurement of similarity-based tie formation	Structural/relational analysis framework
원전	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.	McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: homophily in social networks. Annual Review of Sociology, 27, 415–444.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
별칭	dyad analysis, dyadic data analysis, social relations model, dyad census	homophily measurement, assortative mixing analysis, birds-of-a-feather analysis, tie-similarity analysis	SNA, network analysis, sociometric analysis, relational analysis
관련	4	4	5
요약	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.	Homophily analysis quantifies the tendency of similar individuals to form ties — the principle that 'birds of a feather flock together'. It compares the rate at which people connect with others who share an attribute (race, gender, age, education, attitudes) against what would be expected by chance, distinguishing the homophily that arises merely from group sizes from the genuine, behavior-driven preference for similar others.	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.