LAUSR

Improving the position of minority groups in networks is important, but it is unclear which interventions are effective to achieve this goal. We propose a model to examine network growth interventions and find that even extreme quotas are not enough to increase minority representation in rankings unless they are coupled with the right type of behavioural intervention. Improving the position of minority groups in networks through interventions is a challenge of high theoretical and societal importance. However, a systematic analysis of interventions that alter the network growth process is still missing. In this work, we propose a model to examine how network growth interventions impact the position of minority nodes in degree rankings over time. We distinguish between (i) group size interventions, such as introducing quotas; and (ii) behavioural interventions, such as varying how groups connect to each other. We find that even extreme quotas do not increase minority representation in rankings if the actors in the network do not adopt homophilic behaviour. Thus, interventions need to be coordinated in order to improve the visibility of minorities. In a real-world case study, we explore which interventions can reach gender parity in academia. Our work provides a theoretical and computational framework for investigating the effectiveness of interventions in growing networks.