HNR2021 Workshop 2: Exponential Random Graph Models for Historical Networks

HNR2021 Workshop Day (June 30, 2021)

Workshop 2: Exponential Random Graph Models: Theory and Aplications on Historical Networks

Convenor: Antonio Maria Fiscarelli, University of Luxembourg.

Supported by the Luxembourg National Research Fund (FNR) DTU-DHH, C2DH, CSC-ILIAS, University of Luxembourg, 11, Porte des Sciences, L-4366 Esch-sur-Alzette, Luxembourg

Check our website for more information about the conference: http://hnr2021.historicalnetworkresearch.org/

Description

This workshop will provide an introduction to Exponential Random Graph Mod els (ERGMs), followed by some example applications on historical networks. ERGMs are a family of statistical models that help discover the processes underlying network formation [1–3]. They have been used extensively in social network analysis and are popular in various fields such as sociology [4, 5], archaeology [6], and history [7]. Within this framework, one can:

• Define a model for a network that includes covariates representing features like homophily, mutuality, triad effects, and a wide range of other structural features
• Obtain maximum-likehood estimates for the parameters of the specified model
• Test individual coefficients, assess models for convergence and goodness-of-fit – Simulate new networks from the underlying probability distribution implied by the fitted model

Prerequisites

• Basic concepts of statistics (mean, standard deviation, probability distribution)
• Basic concepts of network analysis (nodes, edges, degree, transitivity) – Basic familiarity with R (network and sna packages)

References

1. Anderson, C.J., Wasserman, S., Crouch, B.: A p* primer: Logit models for social networks. Social networks 21(1) (1999) 37–66

2. Robins, G., Pattison, P., Kalish, Y., Lusher, D.: An introduction to exponential random graph (p*) models for social networks. Social networks 29(2) (2007) 173– 191

3. Robins, G., Snijders, T., Wang, P., Handcock, M., Pattison, P.: Recent developments in exponential random graph (p*) models for social networks. Social networks 29(2) (2007) 192–215

4. Goodreau, S.M., Kitts, J.A., Morris, M.: Birds of a feather, or friend of a friend? using exponential random graph models to investigate adolescent social networks. Demography 46(1) (2009) 103–125

5. Grund, T.U., Densley, J.A.: Ethnic homophily and triad closure: Mapping internal gang structure using exponential random graph models. Journal of Contemporary Criminal Justice 31(3) (2015) 354–370

6. Brughmans, T., Keay, S., Earl, G.: Introducing exponential random graph models for visibility networks. Journal of Archaeological Science 49 (2014) 442–454 7. Breure, A.S., Heiberger, R.H.: Reconstructing science networks from the past. Journal of Historical Network Research 3(1) (2019) 92–117