Literature DB >> 32863704

Network centrality, group density, and strength of social identification in college club sport teams.

Scott Graupensperger1, Michael Panza1, M Blair Evans1.   

Abstract

OBJECTIVE: 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.
METHOD: 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.
RESULTS: 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.
CONCLUSION: Sport is a domain where 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.

Entities:  

Keywords:  Multilevel Modeling; Social Identity; Social Network Analysis; Sport Teams

Year:  2020        PMID: 32863704      PMCID: PMC7453997          DOI: 10.1037/gdn0000106

Source DB:  PubMed          Journal:  Group Dyn        ISSN: 1089-2699


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