Network Statistical Models for Language Learning Contexts: Exponential Random Graph Models and Willingness to Communicate

Abstract

As part of the shift within second language acquisition (SLA) research toward complex systems thinking, researchers have called for investigations of social network structure. One strand of social network analysis yet to receive attention in SLA is network statistical models, whereby networks are explained in terms of smaller substructures of social ties. This article offers an overview and instructive demonstration of exponential random graph models as applied to a cohort of English for Academic Purposes students (N = 75) and their willingness to communicate in the second language (L2 WTC). Results indicate that cross‐cultural ties build off of intracultural ties through triadic closure (meeting through a mutual contact). Furthermore, situational subtypes of L2 WTC are associated with various network tie patterns.