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Web Search Personalization during the US 2020 Election
Ulrich Matter
Roland Hodler
蝌蚪网 Review: Insights (Forthcoming)
Abstract
We study the impact of web search personalization on ideological
segregation in search results. We deploy 150 synthetic internet
users with randomized partisan browsing preferences across 25 US
cities. These users are active during the US 2020 election and
its aftermath. Daily experiments in which the users enter identical
election-related queries provide strong evidence for ideological
segregation in search results across locations with different partisan
leanings, but only limited evidence for ideological segregation within
location across users with different partisan browsing habits. We
discuss the important role of the national and local (online) media
landscape for understanding these results.
