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Ethics and Information Technology

, Volume 15, Issue 3, pp 209–227 | Cite as

Bias in algorithmic filtering and personalization

  • Engin Bozdag
Original Paper

Abstract

Online information intermediaries such as Facebook and Google are slowly replacing traditional media channels thereby partly becoming the gatekeepers of our society. To deal with the growing amount of information on the social web and the burden it brings on the average user, these gatekeepers recently started to introduce personalization features, algorithms that filter information per individual. In this paper we show that these online services that filter information are not merely algorithms. Humans not only affect the design of the algorithms, but they also can manually influence the filtering process even when the algorithm is operational. We further analyze filtering processes in detail, show how personalization connects to other filtering techniques, and show that both human and technical biases are present in today’s emergent gatekeepers. We use the existing literature on gatekeeping and search engine bias and provide a model of algorithmic gatekeeping.

Keywords

Information politics Bias Social filtering Algorithmic gatekeeping 

Notes

Acknowledgments

The author would like to thank Martijn Warnier and Ibo van de Poel for their valuable comments. This research is supported by the Netherlands Organization for Scientific Research (NWO) Mozaiek grant, file number 017.007.111.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Delft University of TechnologyDelftThe Netherlands

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