  Corruptive behaviour in politics limits economic growth, embezzles public
funds, and promotes socio-economic inequality in modern democracies. We analyse
well-documented political corruption scandals in Brazil over the past 27 years,
focusing on the dynamical structure of networks where two individuals are
connected if they were involved in the same scandal. Our research reveals that
corruption runs in small groups that rarely comprise more than eight people, in
networks that have hubs and a modular structure that encompasses more than one
corruption scandal. We observe abrupt changes in the size of the largest
connected component and in the degree distribution, which are due to the
coalescence of different modules when new scandals come to light or when
governments change. We show further that the dynamical structure of political
corruption networks can be used for successfully predicting partners in future
scandals. We discuss the important role of network science in detecting and
mitigating political corruption.
