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To cope with the immense amount of content on the web, search engines often use complex algorithms to personalize search results for individual users. However, personalization of search results has led to worries about the Filter Bubble Effect, where the personalization algorithm decides that some useful information is irrelevant to the user, and thus prevents them from locating it. In this paper, we propose a novel methodology to explore the impact of location-based personalization on Google Search results. Assessing the relationship between location and personalization is crucial, since users' geolocation can be used as a proxy for other demographic traits, like race, income, educational attainment, and political affiliation. In other words, does location-based personalization trap users in geolocal Filter Bubbles?
Kliman-Silver et al. (Tue,) studied this question.