CEDRR talk: Analyzing non-local influence processes in dynamic networks

Speaker: Daniel Gotthardt, Universität Hamburg
Chair: David Zbíral, Masaryk University

Generative network models have significantly advanced our understanding of complex systems by exploring how local interactions give rise to broader structures and inform actor decisions. While mechanisms like dyadic reciprocity and triadic closure or contagion are well-known, many networks exhibit non-local processes that are not easily captured by current longitudinal models. In this lecture, I'll use organizational fields as a key example to explore how concepts from institutional theory—specifically mimetic, normative, and coercive isomorphism— indicate that organizations may evolve due to influences from central actors or through imitation of similar entities, irrespective of network distances. I will present simulations on synthetic and observed networks to illustrate these dynamics, highlighting the need for models that capture influences beyond local neighborhoods. Additionally, I will examine how models like the stochastic actor-oriented model can be extended to better understand these non-local influence dynamics, accounting also for micro-dynamics and conjugate selection effects.

Bio
Daniel Gotthardt studied sociology and mathematics at the University of Hamburg and currently is involved in a research project about the statistical modeling of organizations’ decarbonization discourses and the impact of extreme climate events on organizational field networks. His research focuses on meta-theoretical and methodological questions, like the quantitative modelling of variability across contexts, as well as longitudinal network analysis of the dynamics of non-local processes. Additionally, he is developing methods for effect sizes to facilitate comparisons between network models.

The lecture will also be streamed on the following Zoom link: https://cesnet.zoom.us/j/94613802750?pwd=bcGyexOus5dTq6FmVaqGJhbX31bsaa.1