Title: Social Network Spatial Model.

Authors: Ciminelli, Joseph T; Love, Tanzy; Wu, Tong Tong

Published In Spat Stat, (2019 Mar)

Abstract: Our work is motivated by a desire to incorporate the vast wealth of social network data into the framework of spatial models. We introduce a method for modeling the spatial correlations that exist over a social network. In particular, we model attributes measured for each member of the network as a continuous process over the social space created by their connections. Our method simultaneously models the unobserved locations of network members in social space and the spatial process that exists over that space based on the observed network connections and nodal attributes. The model is evaluated through simulation studies and applied to the importance ranking for a network of emergency response organizations and the physical activity habits of teenage girls. The introduced methods incorporate network data into the spatial framework, expanding traditional models to include this often relevant source of additional information.

PubMed ID: 31456909

MeSH Terms: No MeSH terms associated with this publication