Modeling Dynamic Social Networks of Children in After-School Care Programs

Abstract

Problem: There is a lack of work examining children’s social networks outside of the classroom and dynamic network analysis with small networks is one way to see how children influence one another socially over time. The current study utilized an existing database of two after-school care programs represented as networks of friendship connections between children in each program. The children were aged 5 to 12 years old and information was collected at three time points on their activity levels, who they were friends with in the program, and other covariates, such as sex, race/ethnicity, and obesity. We examined whether or not children influence one another’s activity levels through their direct friendship connections. Methods: Dynamic social network analyses were deployed using three different models: separable temporal exponential random graph models (STERGMs), stochastic actor-based models to replicate the original analyses, and models based on the work of Kindermann (2007). Summary: Findings indicate that activity levels are not important when children are forming friendships, but having a friend with a similar level of activity makes a child less likely to end the friendship.