Measuring Political Personalization of Google News Search

Abstract

There is a growing concern about the extent to which algorithmic personalization limits people’s exposure to diverse viewpoints, thereby creating “filter bubbles" or “echo chambers." Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user’s browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet" auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship.