Locally Ensconced and Globally Integrated: How Positions in Network Structure Relate to a Language-Based Model of Group Identification

Shifting attachments to social groups are a constant in the modern era. What accounts for variation in the strength of group identification? Whereas prior work has emphasized group-level properties and individual differences, this article instead highlights the role of positions within network structure. Distilling insights from prior work on networks and identity, the authors propose that identification strength is positively related to network cohesion—having contacts who are mutually interconnected. Departing from prevailing accounts, they further propose that identification strength can separately arise through network range—having contacts who inhabit a broad range of network communities. Using the tools of computational linguistics to develop a language-based measure of identification, they find consistent support for the theory using pooled data of internal communications from three disparate organizations.