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.

翻译：本研究通过分析巴西、英国和美国的搜索结果，考察了谷歌搜索算法对新闻多样性的影响。它探讨了谷歌系统如何优先偏向有限数量的新闻媒体。该研究利用算法审计技术，采用赫芬达尔-赫希曼指数（HHI）和基尼系数衡量来源集中度，揭示了显著的集中化趋势。研究强调了跨多个搜索查询进行横向分析的重要性，因为仅关注单个结果页面可能会掩盖这些模式。研究评估了流行度、政治偏见和时效性等因素对新闻排名的影响。研究结果表明，搜索结果存在轻微的左倾偏见，并倾向于流行且通常是全国性的媒体。这种偏见，加上优先呈现近期内容的倾向，表明谷歌算法可能强化了现有的媒体不平等。通过分析迄今为止最大的数据集——221,863个搜索结果，本研究就算法如何塑造公众获取多样化新闻来源提供了全面、纵向的洞察。