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Are Search Engines Biased? Detecting and Reducing Bias using Meta Search Engines by Patrick Maillé; Gwen Maudet; Mathieu Simon; Bruno Tuffin is a Business, Management and Accounting article available to read on EtoBox.

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The search neutrality debate stems from content or service providers complaining about being discriminated and ranked unfairly low by search engines, raising the need for methodologies and tools to verify bias in search engine rankings. For that purpose, we propose in this paper a simple yet effective framework based on the comparison of the results provided by several search engines, and build the corresponding tool to carry out a campaign of tests. The main objectives are to develop an interpretable model of search engine behaviors and to design statistical tests pointing out suspicious instances as possible bias, without knowing the detailed ranking algorithms implemented by search engines. Our approach consists in reasoning in terms of the visibility that search engines give webpages when ranking them among their results; different types of possible bias can then be detected using statistical tests for outlier detection. We apply this methodology to a test campaign over the most searched terms, which highlights some similarities and discrepancies among search engines, and possible instances of bias. Our approach can be of interest to regulators or any actor in the Internet, and

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Author

Patrick Maillé; Gwen Maudet; Mathieu Simon; Bruno Tuffin

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Business, Management and Accounting (Social Sciences)