The Role of Search Engines in the Amplification and Suppression of LGBTIQ+ Polarization

TL;DR

This study investigates how search engine algorithms influence the exposure of users to polarizing LGBTIQ+ content, revealing that the choice of search engine and query polarity significantly affect content polarization in Europe.

Contribution

It provides a large-scale quantitative analysis of search engine biases and their role in amplifying or suppressing LGBTIQ+ polarization, focusing on the UK, Germany, and France.

Findings

Search engine choice is the primary factor in exposure to polarizing content.

Query polarity significantly influences the likelihood of encountering polarizing material.

Location and language have minor effects compared to search engine algorithms.

Abstract

Search engines are used and trusted by hundreds of millions of people every day. However, the algorithms used by search engines to index, filter, and rank web content are inherently biased, and will necessarily prefer some views and opinions at the expense of others. In this article, we examine how these algorithmic biases amplify and suppress polarizing content. Polarization refers to a shift toward and the acceptance of ideological extremes. In Europe, polarizing content in relation to LGBTIQ+ issues has been a feature of various ideological and political conflicts. Although past research has focused on the role of social media in polarization, the role of search engines in this process is little understood. Here, we report on a large-scale study of 1.5 million search results responding to neutral and negative queries relating to LGBTIQ+ issues. Focusing on the UK, Germany, and France, our analysis shows that the choice of search engine is the key determinant of exposure to polarizing content, followed by the polarity of the query. Location and language, on the other hand, have a comparatively minor effect. Consequently, our findings provide quantitative insights into how differences between search engine technologies, rather than the opinions, language, and location of web users, have the greatest impact on the exposure of web users to polarizing Web content.