Merging textual and numerical databases: a steppingstone for statistical analyses of illegal events

This paper aims to define a methodological path—merging judgments and official statisti-cal data—to organize complete, objective, and reliable data in a database, thus simplifyingthe analysis of illegal social phenomena. Judiciary judgments are a new data source: theydeal with illegal events that describe social phenomena even if they are only the "illegal"ones—and contain objective and reliable data and information. Judiciary judgments arealso texts, so the first step is a statistical textual analysis and text mining techniques todiscover information and organize it in a statistical database. The final database is obtainedby integrating numerical data from other information sources. It therefore has statisticalproperties such as reliability, completeness and updating. Subsequent statistical analyses ormodelling are then possible based on the entire set or subsets of data adequately extractedfrom the implemented statistical database. We present some results obtained from judgments about corruption in order to demonstrate the advantages of linking textual data-bases (textual analyses on judgments) and numerical databases (from ISTAT). The pro-posed methodology can benefit different stakeholders, such as researchers, policymakers,and other enforcement actors. It is independent of the specific software used and remainsvalid when applied to other illegal activities (e.g., organized crime, tax crime, and moneylaundering). Furthemore, the results may be even more effective if the institutional actorsinvolved have access to judgments at all levels, thus overcoming potential privacy concerns. The methodology could also be used to support evidence-based policy in the fightagainst crime and illegal activities.