In this paper, the authors focus on the use of data mining techniques to unveil complex anomalous spatiotemporal patterns of sexual violence.
When sexual violence is a product of organized crime or social imaginary, the links between sexual violence episodes can be understood as a latent structure. With this assumption in place, we can use data science to uncover complex patterns. In this paper the authors focus on the use of data mining techniques to unveil complex anomalous spatiotemporal patterns of sexual violence. They illustrate their use by analyzing all reported rapes in El Salvador over a period of nine years. Through their analysis, they can provide evidence of phenomena that, to the best of the authors’ knowledge, have not been previously reported in literature. They devote special attention to a pattern the authors discovered in the East, where underage victims report their boyfriends as perpetrators at anomalously high rates. Finally, the authors explain how such analyzes could be conducted in real-time, enabling early detection of emerging patterns to allow law enforcement agencies and policymakers to react accordingly. (Published abstract provided)