The network autocorrelation model using two-mode data: Affiliation exposure and potential bias in the autocorrelation parameter

The network autocorrelation model has been a workhorse for modeling network influences on individual behavior. The standard network approaches to mapping social influence using network measures, however, are limited to specifying an influence weight matrix (W) based on a single mode network. Additionally, it has been demonstrated that the estimate of the autocorrelation parameter of the network effect tends to be negatively biased as the density in W matrix increases. The current study