A multilevel network study of the effects of delinquent behavior on friendship evolution

TLDR

The study applies a multilevel network approach to investigate how delinquent behavior influences friendship formation. Stochastic actor‑oriented models estimated via Markov chain Monte Carlo are used across 19 school classes to model network evolution. Results show that similarity in delinquent behavior increases both tie formation and dissolution, a finding that challenges existing criminological theories. Keywords: Actor‑oriented Model, Longitudinal Data, Social Networks, Criminology, Adolescents.

Abstract

Abstract A multilevel approach is proposed to the study of the evolution of multiple networks. In this approach, the basic evolution process is assumed to be the same, while parameter values may differ between different networks. For the network evolution process, stochastic actor-oriented models are used, of which the parameters are estimated by Markov chain Monte Carlo methods. This is applied to the study of effects of delinquent behavior on friendship formation, a question of long standing in criminology. The evolution of friendship is studied empirically in 19 school classes. It is concluded that there is evidence for an effect of similarity in delinquent behavior on friendship evolution. Similarity of the degree of delinquent behavior has a positive effect on tie formation but also on tie dissolution. The last result seems to contradict current criminological theories, and deserves further study. Keywords: Actor-oriented ModelLongitudinal DataSocial NetworksCriminologyAdolescents