ScholarGate
Asistent
Regression modelSocial influence / peer effects modeling

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.

Otvorite u MethodMindUskoroПримените, упоредите, добијте смернице
Алати и ресурси
Preuzmi slajdove
Учите и истражујте
VideoUskoro

Pročitajte celu metodu

Samo za članove

Prijavite se besplatnim nalogom da biste pročitali ovaj odeljak.

Prijavite se

Mapa metoda

Okruženje srodnih metoda — izaberite čvor da biste istraživali.

Izvori

  1. 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
  2. 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

Kako citirati ovu stranicu

ScholarGate. (2026, June 22). Network Autocorrelation Model of Social Influence. ScholarGate. https://scholargate.app/sr/sociology/network-autocorrelation-model

Koja metoda?

Postavite ovu metodu pored njoj najbližih srodnika i čitajte ih uporedo — biblioteka polaže knjige na sto; izbor je na vama.

Uporedi uporedo

Citirana u

ScholarGateNetwork Autocorrelation Model (Network Autocorrelation Model of Social Influence). Preuzeto 2026-06-24 sa https://scholargate.app/sr/sociology/network-autocorrelation-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026