Network Centrality, Group Density, and Strength of Social Identification in College Club Sport Teams

Scott Graupensperger, Michael Panza, M. Blair Evans

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

With the underlying rationale that social identification is related to psychological health and well-being, we aimed to understand how social connections and group structure within college club sport teams relate to students' perceptions of social identification. We sampled 852 student-athletes from 35 intact same-sex college club sport teams. Using social network analyses derived from teammates' reports of connections with one another (i.e., time spent outside of sport, and teammate friendships), we computed: outdegree centrality (i.e., self-reported connections with teammates), indegree centrality (i.e., nominations from others), and group-level density. Multilevel models were fit to test the relative effects of outdegree centrality, indegree centrality, and group-level team density on athletes' social identification strength. Outdegree centrality, indegree centrality, and team density were all positively related to the strength of athletes' social identification with their sport team. Examining model results step by step, incoming nominations of social connections (i.e., indegree) were associated with social identification beyond the effects of self-reported outdegree centrality. Furthermore, team-level density was significantly related to social identification after accounting for the individual-level effects of centrality. Sport is a domain in which participants can build social connections with peers, and sport groups offer a salient source for social identification. The current findings indicate that athletes who have greater social connections with teammates may form a stronger sense of social identification. Alongside theoretical contributions to a social identity approach to studying small groups, the current study highlights the utility of studying small groups using social network methodologies.

Original languageEnglish (US)
JournalGroup Dynamics
DOIs
StateAccepted/In press - 2019

All Science Journal Classification (ASJC) codes

  • Social Psychology
  • Applied Psychology

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