Auditing Google's Search Algorithm: Measuring News Diversity Across Brazil, the UK, and the US

Fuente: arXiv
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Autores principales: Hernandes, Raphael, Corsi, Giulio
Formato: Preprint
Publicado: 2024
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author Hernandes, Raphael
Corsi, Giulio
author_facet Hernandes, Raphael
Corsi, Giulio
contents This study examines the influence of Google's search algorithm on news diversity by analyzing search results in Brazil, the UK, and the US. It explores how Google's system preferentially favors a limited number of news outlets. Utilizing algorithm auditing techniques, the research measures source concentration with the Herfindahl-Hirschman Index (HHI) and Gini coefficient, revealing significant concentration trends. The study underscores the importance of conducting horizontal analyses across multiple search queries, as focusing solely on individual results pages may obscure these patterns. Factors such as popularity, political bias, and recency were evaluated for their impact on news rankings. Findings indicate a slight leftward bias in search outcomes and a preference for popular, often national outlets. This bias, combined with a tendency to prioritize recent content, suggests that Google's algorithm may reinforce existing media inequalities. By analyzing the largest dataset to date -- 221,863 search results -- this research provides comprehensive, longitudinal insights into how algorithms shape public access to diverse news sources.
format Preprint
id arxiv_https___arxiv_org_abs_2410_23842
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Auditing Google's Search Algorithm: Measuring News Diversity Across Brazil, the UK, and the US
Hernandes, Raphael
Corsi, Giulio
Computers and Society
Artificial Intelligence
Information Retrieval
This study examines the influence of Google's search algorithm on news diversity by analyzing search results in Brazil, the UK, and the US. It explores how Google's system preferentially favors a limited number of news outlets. Utilizing algorithm auditing techniques, the research measures source concentration with the Herfindahl-Hirschman Index (HHI) and Gini coefficient, revealing significant concentration trends. The study underscores the importance of conducting horizontal analyses across multiple search queries, as focusing solely on individual results pages may obscure these patterns. Factors such as popularity, political bias, and recency were evaluated for their impact on news rankings. Findings indicate a slight leftward bias in search outcomes and a preference for popular, often national outlets. This bias, combined with a tendency to prioritize recent content, suggests that Google's algorithm may reinforce existing media inequalities. By analyzing the largest dataset to date -- 221,863 search results -- this research provides comprehensive, longitudinal insights into how algorithms shape public access to diverse news sources.
title Auditing Google's Search Algorithm: Measuring News Diversity Across Brazil, the UK, and the US
topic Computers and Society
Artificial Intelligence
Information Retrieval
url https://arxiv.org/abs/2410.23842