Attachment Styles Predict Personal Network Structure Better Than Big Five Traits

Research on individual differences in social network analysis has primarily focused on how personality traits influence individuals’ positions and behaviors within social structures. However, attachment research has consistently shown that attachment styles strongly affect how people form and maintain their interpersonal relationships. This study examined how attachment styles relate to different types of individual personal networks. A classification of personal networks was developed based on structural indicators of cohesion, transitivity, and subgroup configuration, among other measures. Density, fragmentation, and centralization emerged as the most discriminant metrics for clustering solutions. Results indicated that attachment styles have greater explanatory power than the Big Five model in accounting for distinct relational configurations. Specifically, secure attachment was associated with dense, noncentralized, and supportive personal networks, whereas avoidant attachment and openness to experience were linked to fragmented, modular, and less supportive networks. Sociodemographic variables showed the highest predictive value for the type of personal network.