A multidisciplinary survey on discrimination analysis

The collection and analysis of observational and experimental data represent the main tools for assessing the presence, the extent, the nature, and the trend of discrimination phenomena. Data analysis techniques have been proposed in the last fifty years in the economic, legal, statistical, and, recently, in the data mining literature. This is not surprising, since discrimination analysis is a multi-disciplinary problem, involving sociological causes, legal argumentations, economic models, statistical techniques, computational issues. The objective of this survey is to provide a guidance and a glue for researchers and anti-discrimination data analysts on concepts, problems, application areas, datasets, methods and approaches from a multidisciplinary perspective. We organize the approaches according to their method of data collection as observational, quasi-experimental and experimental studies. A fourth line of recently blooming research on knowledge discovery based methods is also covered. Observational methods are further categorized on the basis of their application context: labor economics, social profiling, consumer markets, and others.