Mafia language analysis and detection using Computational Linguistics tools

Abstract

Hate Speech and violent language detection with Natural Language Processing (NLP) tools are up-to-theminute. If such technology could be applied to criminal jargon, it would give law enforcement agencies new resources to speed up investigations and evidence gathering against organised crime. This paper foresees the innovative approach of using computational tools and Machine Learning (ML) to detect Mafia language in electronic surveillance transcriptions used in Italian courts as evidence. Starting from a null hypothesis, this research will try to demonstrate the alternative hypothesis, that the variable Mafia and no-Mafia language can be differentiated. The first part of the investigation will determine the extent to which NLP tools detect Mafia language features, contrasting them with no-Mafia criminal jargon. The second part will describe an experiment to demonstrate how ML tools can recognise the Mafia variable for investigative purposes. In the conclusions, the effectiveness of the proposal as a pioneering method to fight the Mafia using its language will be discussed, defending the work of linguists and leaving the door open to new perspectives.