Modeling social networks
Abstract
In this talk, I describe an approach to modeling social networks that has its origins in statistical physics and models for interactive spatial processes in plant ecology. The approach construes global network structure as the outcome of dynamic, potentially realisation-dependent processes occurring within local neighbourhoods of a network. I describe a hierarchy of models implied by the approach and note that they can be estimated from partial network data structures obtained through certain types of network sampling schemes. I give two illustrations of how these models enhance our capacity to model observed network structures.
Online (Zoom) Link to register: https://iu.zoom.us/webinar/register/WN_QXAmc5gvRGOWGRwV6rKDbw
Short Bio
Pip is a quantitative psychologist by background who spent much of her career at the University of Melbourne before joining the University of Sydney as Deputy Vice-Chancellor Education in 2014 until her retirement in 2021. The primary focus of Pip’s research has been the development of mathematical and statistical models for social networks and network processes, with applications to areas such as the transmission of infectious diseases and community recovery following bushfire. Pip was elected a Fellow of the Academy of the Social Sciences in Australia in 1995, of the Royal Society of NSW in 2017 and of the Network Science Society in 2025. She received the Simmel Award from the International Network for Social Network Analysis in 2002 and became an Officer of the Order of Australia in 2015. She is an Emeritus Professor at the Universities of Melbourne and Sydney.