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International Conference on Social Informatics

SocInfo 2019: Social Informatics pp 253–266Cite as

You Can’t See What You Can’t See: Experimental Evidence for How Much Relevant Information May Be Missed Due to Google’s Web Search Personalisation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11864))

Abstract

The influence of Web search personalisation on professional knowledge work is an understudied area. Here we investigate how public sector officials self-assess their dependency on the Google Web search engine, whether they are aware of the potential impact of algorithmic biases on their ability to retrieve all relevant information, and how much relevant information may actually be missed due to Web search personalisation. We find that the majority of participants in our experimental study are neither aware that there is a potential problem nor do they have a strategy to mitigate the risk of missing relevant information when performing online searches. Most significantly, we provide empirical evidence that up to \(20\%\) of relevant information may be missed due to Web search personalisation. This work has significant implications for Web research by public sector professionals, who should be provided with training about the potential algorithmic biases that may affect their judgments and decision making, as well as clear guidelines how to minimise the risk of missing relevant information.

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Notes

  1. 1.

    Numbers for market share as per 2018 market research reported in https://www.smartinsights.com/search-engine-marketing/search-engine-statistics/.

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Author information

Authors and Affiliations

  1. School of Information Management, Victoria University of Wellington, Wellington, New Zealand

    Cameron Lai & Markus Luczak-Roesch

Authors
  1. Cameron Lai
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  2. Markus Luczak-Roesch
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Corresponding author

Correspondence to Markus Luczak-Roesch .

Editor information

Editors and Affiliations

  1. Qatar Computing Research Institute, Doha, Qatar

    Ingmar Weber

  2. Qatar Computing Research Institute, Doha, Qatar

    Kareem M. Darwish

  3. University of Koblenz-Landau, Koblenz, Germany

    Claudia Wagner

  4. Max Planck Institute for Demographic Research, Rostock, Germany

    Emilio Zagheni

  5. Northeastern University, Boston, MA, USA

    Laura Nelson

  6. Max Planck Institute for Demographic Research, Rostock, Germany

    Samin Aref

  7. GESIS-Leibniz Institute for the Social Sciences, Cologne, Germany

    Fabian Flöck

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Lai, C., Luczak-Roesch, M. (2019). You Can’t See What You Can’t See: Experimental Evidence for How Much Relevant Information May Be Missed Due to Google’s Web Search Personalisation. In: Weber, I., et al. Social Informatics. SocInfo 2019. Lecture Notes in Computer Science(), vol 11864. Springer, Cham. https://doi.org/10.1007/978-3-030-34971-4_17

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  • DOI: https://doi.org/10.1007/978-3-030-34971-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34970-7

  • Online ISBN: 978-3-030-34971-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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