核心概念
Relational event simulations can be used to assess the goodness-of-fit of relational event models and to develop and test social theories about interaction dynamics in social networks.
要約
The article introduces general frameworks to simulate relational event networks under the dyadic (Butts, 2008) and actor-oriented (Stadtfeld and Block, 2017) relational event models. It then demonstrates three key applications of these simulation frameworks:
Assessing goodness-of-fit: Simulated sequences can be used to evaluate how well a fitted relational event model captures important network characteristics in the observed data, such as degree distributions, density, triadic structures, and inter-event time distributions.
Developing theories: Relational event simulations provide a flexible tool to test and refine theoretical models about the social mechanisms driving interactions in social networks. Simulations can be used to study the emergence of social phenomena, evaluate boundary conditions of theories, and incorporate timing and dynamism into theoretical frameworks.
Evaluating network interventions: Relational event simulations can be used to explore the temporal dynamics of social networks under different intervention scenarios, such as investigating how quickly networks respond to interventions, how long interventions need to be carried out to achieve desired outcomes, and whether the effects of interventions persist over time.
The article demonstrates the application of these simulation-based approaches using an email dataset from the Enron corporation and an example of simulating the Optimal Distinctiveness Theory of group formation.
統計
"The Enron email dataset contains approximately 5000 events from January 1, 2001 - August 30, 2001."
"The simulation of the Optimal Distinctiveness Theory was conducted on a network of 30 actors with a binary attribute, with the proportion of actors with each attribute varied from 0.1 to 0.5."
引用
"Simulation-based methods can be used to assess model fit in an absolute sense by assessing whether important network characteristics in the data are also present in simulated data using the fitted model."
"Relational event simulations can be a powerful tool to develop social theories by providing a way to test and refine theoretical models in a controlled and systematic way."
"By simulating network interaction patterns across a range of parameter values or initial conditions, it can be assessed beyond which (combinations of) values the model starts to generate non-sensical or unrealistic dynamics."