Network Autocorrelation Model
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.
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Sources
- Leenders, R. Th. A. J. (2002). Modeling social influence through network autocorrelation: Constructing the weight matrix. Social Networks, 24(1), 21–47. DOI: 10.1016/S0378-8733(01)00049-1 ↗
- Doreian, P. (1980). Linear models with spatially distributed data: Spatial disturbances or spatial effects? Sociological Methods & Research, 9(1), 29–60. DOI: 10.1177/004912418000900102 ↗
How to cite this page
ScholarGate. (2026, June 22). Network Autocorrelation Model of Social Influence. ScholarGate. https://scholargate.app/en/sociology/network-autocorrelation-model
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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