Citation

Pitoura E, Tsaparas P, Flouris G, Fundulaki I, Papadakos P, Abiteboul S, Weikum G. SIGMOD Rec. 2018; 46(4): 16-21.

Copyright

(Copyright © 2018, Special Interest Group on Management of Data (SIGMOD), Association for Computing Machinery (ACM))

DOI

10.1145/3186549.3186553

PMID

unavailable

Abstract

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.

Language: en