Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Electronic Commerce Research and Applications Year : 2022

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.
Fichier principal
Vignette du fichier
main.pdf (918.69 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03150446 , version 1 (23-02-2021)

Licence

Identifiers

Cite

Patrick Maillé, Gwen Maudet, Mathieu Simon, Bruno Tuffin. Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines. Electronic Commerce Research and Applications, 2022, ⟨10.1016/j.elerap.2022.101132⟩. ⟨hal-03150446⟩
268 View
1712 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More