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When talking about co-offending and organized crime, multiple avenues have been explored. These include longitudinal research on juvenile delinquency and the onset, criminal offenders’ history, like sequences of offending, risk factors in criminal group membership, social link opportunities and affiliation theories such as developmental and life-course criminology, recruitment and intergenerational continuity. The purpose of this presentation is to focus on the social network perspective and aims to provide a social context to understand the influence of affiliation on offenders joining organized criminal groups. Data is based on police arrests in North Carolina from 2007 to 2017 (n = 45,283 individuals). It was divided into four equal temporal parts in which offenders were possibly arrested multiple times in different periods. Every period is then analyzed with a network analysis followed by a community detection algorithm. This method allows to statistically identify affiliated offenders and observing the criminal career trajectory and situational context around affiliation trajectories. Results show that both individual and structural characteristics influence gang affiliation. Past affiliation may be as significant as past arrests in predicting affiliation trajectories and criminal career patterns.