Using Social Network Analysis to Examine the Collective Dynamics of Smoking Behavior by Isabel Arvelo ’23, Statistics Colloquium, Wednesday, February 15, 1:10 – 1:50 pm, North Science Building 114, Wachenheim.
Abstract: How do the people you surround yourself with affect your health? We live in a highly connected world, embedded in structural patterns that have important consequences on how we live our lives and make decisions. Social network analysis (SNA) examines the links between elements within a system, utilizing networks and graph theory to understand how things such as information, marketing, and illness flow through social interaction. After introducing fundamental SNA terminology and methods, we will go over how to graph networks using the Kamada-Kawai algorithm and discuss a public health application that uses network analytic methods and a longitudinal logistic regression model to study the smoking behavior and social network ties of a densely interconnected social network within the Framingham Heart Study.