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Topic:
Some Aspects of Statistical Modelling of Networks
Abstract:
Social network analysis (SNA) is going from strength to strength, gathering currency and offering novel and relevant insights. In recent years the class of statistical models for networks that is commonly referred to as exponential random graph (ERG) models has become increasingly more popular. For many applied network scientists ERG models are becoming something of a go-to tool for analysing network data – but what are they? In this talk we will revisit some of the foundations of ERG models and discuss the implications and interpretations associated with dependence and homogeneity assumptions. For the latter we will also introduce a methodology for detecting and investigating outliers and influential observations in the ERG framework. This allows us to investigate the fundamental question of how different can a node be from other nodes due solely to endogenous dynamics.
Speaker:
Dr Johan Koskinen
Department of Social Statistics
University of Manchester
About the
Speaker:
Dr Johan Koskinen joined the Department of Social Statistics at the University of Manchester in 2011 having previously worked at the Universities of Stockholm, Melbourne and Oxford. Dr Koskinen has contributed extensively to methodological development in social network analysis to enabled innovative applications by several disciplines. He is one of the co-authors of the RSiena statistical network analysis package for longitudinal network analysis and a contributor to the MPnet software package, one of the most commonly used statistical software packages for network analysis. His methodological contributions are often developed in collaboration over substantive research projects with applied researchers and he is active in disseminating best practices through frequent workshops. He has also co-written two books on social network research methods aimed at practitioners. One of them a book on exponential random graph models (Cambridge University Press) that was awarded the 2016 Harrison White Book Award by the American Sociological Association. His current research concentrates on extending current statistical methodology for modelling social interaction to social networks of multiple types of nodes using data collated and collected from different sources.
