On Measuring Bias in Online Information

Evaggelia Pitoura (1) , Panayiotis Tsaparas (1) , Giorgos Flouris (2) , Irini Fundulaki (2) , Panagiotis Papadakos (2) , Serge Abiteboul (3, 4) , Gerhard Weikum (5)

1 Department of Computer Science [Ioannina]
2 ICS-FORTH - Institute of Computer Science [FORTH, Heraklion]
3 VALDA - Value from Data
4 ENS-PSL - École normale supérieure - Paris
5 Max-Planck-Institut

Bias in online information has recently become a pressing issue, with search engines, social networks and recommendation services being accused of exhibiting some form of bias. In this vision paper, we make the case for a systematic approach towards measuring bias. To this end, we discuss formal measures for quantifying the various types of bias, we outline the system components necessary for realizing them, and we highlight the related research challenges and open problems.

Domaines: Base de données [cs.DB]

Evaggelia Pitoura, Panayiotis Tsaparas, Giorgos Flouris, Irini Fundulaki, Panagiotis Papadakos, et al.. On Measuring Bias in Online Information. SIGMOD record, 2018, pp.1-6. ⟨hal-01638069v2⟩