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Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines

Abstract : The search neutrality debate stems from content or service providers complaining about being discriminated and therefore losing market shares due to an unfairly low ranking given by search engines. Those questions stress the need for methodologies and tools to verify bias in search engine rankings and analyze their potential impact. We develop in this paper a simple yet effective framework comparing the results of existing search engines. We present statistical tests based on outlier detection pointing out potential biases, and introduce two meta engines aiming at reducing bias. All this is implemented in a publicly-available tool from which extensive comparisons and bias investigations are carried out.
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Contributor : Bruno Tuffin Connect in order to contact the contributor
Submitted on : Tuesday, February 23, 2021 - 6:36:37 PM
Last modification on : Monday, April 4, 2022 - 9:28:24 AM
Long-term archiving on: : Monday, May 24, 2021 - 8:52:21 PM


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  • HAL Id : hal-03150446, version 1


Patrick Maillé, Gwen Maudet, Mathieu Simon, Bruno Tuffin. Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines. 2021. ⟨hal-03150446⟩



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