Linganisha mbinu

	Network Autocorrelation Model	Homophily Analysis
Nyanja	Sociology	Sociology
Familia	Regression model	Process / pipeline
Mwaka wa asili	1980 (spatial/network models); 2002 (weight matrix)	1954 (concept); 2001 (synthesis)
Mwanzilishi	Patrick Doreian; Roger Leenders (weight-matrix synthesis)	Lazarsfeld & Merton (concept); McPherson, Smith-Lovin & Cook (synthesis)
Aina	Regression with an autoregressive term on a network weight matrix	Measurement of similarity-based tie formation
Chanzo asilia	Leenders, R. Th. A. J. (2002). Modeling social influence through network autocorrelation: Constructing the weight matrix. Social Networks, 24(1), 21–47.	McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: homophily in social networks. Annual Review of Sociology, 27, 415–444.
Majina mbadala	network effects model, social influence model, network disturbances model, autoregressive network model	homophily measurement, assortative mixing analysis, birds-of-a-feather analysis, tie-similarity analysis
Zinazohusiana	4	4
Muhtasari	The network autocorrelation model adapts spatial-econometric regression to social networks to estimate peer influence: it explains an actor's outcome — an attitude, behavior, or performance — as a function of their own covariates plus a weighted average of their network partners' outcomes. The autocorrelation parameter ρ captures the strength of social influence, and the network weight matrix W encodes who influences whom and how strongly.	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.