András Vörös
Department of Social Statistics, University of Manchester
SOST71032 Social Network AnalysisInternally Assure the Quality of Assessment
Introduction to Exponential Random Graph Models (ERGMs)
The network-level model
(Thanks to Bálint Néray and Zsófia Boda for a lot of materials on these slides!)
Quick recap about the intuition behind ERGMs
The network-level model
The tie-level model
Parameter interpretation
Estimation
Outline
2
“Exponential random graph models (ERGMs) are statistical models for network
structure, permitting inferences about how network ties are patterned.”
(Lusher, Koskinen & Robins 2013, Chapter 2)
Goal:
to understand an observed network structure (nb: not to predict single network ties!)
to find underlying processes creating and maintaining the network-based social system
Tie-based approach – ERGMs do not model individual outcomes (though see
extensions)
ERGMs without symbols – recap
3
The rationale behind ERGMs
4
The rationale behind ERGMs
5
The rationale behind ERGMs
Network ties can be explained…
6
The rationale behind ERGMs
Network ties can be explained…
… with attributes of the sender and receiver nodes…
7
The rationale behind ERGMs
Network ties can be explained…
… with attributes of the sender and receiver nodes…
… and with the structure of
their local network neighborhood.
8
The rationale behind ERGMs
Network ties can be explained…
… with attributes of the sender and receiver nodes…
… and with the structure of
their local network neighborhood.
Flexibility regarding the “local
network neighborhood” part.
9
Theories and mechanisms of network tie formation
Lusher, Koskinen & Robins 2013, p. 24
10
The network-level model
11
The network-level model