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Chapter 6
Discrimination Data Analysis:
A Multi-disciplinary Bibliography
Andrea Romei and Salvatore Ruggieri
Abstract.
Discrimination data analysis has been investigated for the last fifty years
in a large body of social, legal, and economic studies. Recently, discrimination
discovery and prevention has become a blooming research topic in the knowledge
discovery community. This chapter provides a multi-disciplinary annotated bibliog-
raphy of the literature on discrimination data analysis, with the intended objective
to provide a common basis to researchers from a multi-disciplinary perspective. We
cover legal, sociological, economic and computer science references.
6.1
Introduction
Discrimination refers to an unjustified distinction of treatment on the basis of any
physical or cultural trait, such as gender, race, religion or sexual orientation. The
problems of assessing the presence, the extent, the nature, and the trend of discrim-
ination are then of primary importance. In the last fifty years, such problems have
been investigated from social, legal, economic, and, recently, from a computer sci-
ence perspective. The issues of data collection and data analysis are persistent, uni-
fying themes along all the perspectives. We present an annotated multi-disciplinary
bibliography specifically focusing on “data-driven”, or empirical, or analytical, ap-
proaches. The ease of data storage and retention, the ever increasing computing
power, the development of intelligent data analysis and mining techniques make it
possible to apply “in-the-large” and to improve over classical statistical and econo-
metric techniques. The reference literature, however, is abundant and spread over
publications of many disciplines, as witnessed by our references: social sciences,
psychology, economics, finance, health research, housing and urban development,
statistics, biometrics, econometrics and data mining.
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