On Measuring Bias in Online Information

Pitoura, Evaggelia; Tsaparas, Panayiotis; Flouris, Giorgos; Fundulaki, Irini; Papadakos, Panagiotis; Abiteboul, Serge; Weikum, Gerhard

doi:10.1145/3186549.3186553

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On Measuring Bias in Online Information

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Weikum, Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Pitoura, E., Tsaparas, P., Flouris, G., Fundulaki, I., Papadakos, P., Abiteboul, S., et al. (2017). On Measuring Bias in Online Information. ACM SIGMOD Record, 46(4), 16-21. doi:10.1145/3186549.3186553.

Cite as: https://hdl.handle.net/21.11116/0000-0000-EA0F-9

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.