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.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Ramani ya mbinu
Jirani ya mbinu zinazohusiana — chagua nodi ili kuchunguza.
Vyanzo
- 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 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 22). Network Autocorrelation Model of Social Influence. ScholarGate. https://scholargate.app/sw/sociology/network-autocorrelation-model
Mbinu ipi?
Weka mbinu hii kando ya jamaa zake wa karibu na uzisome bega kwa bega — maktaba huweka vitabu mezani; uamuzi ni wako.
- Homophily AnalysisSociology↔ linganisha
- MRQAP Network RegressionSociology↔ linganisha
- Uchambuzi wa Mitandao ya KijamiiUchanganuzi wa Mitandao↔ linganisha
- Stochastic Actor-Oriented ModelSociology↔ linganisha
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