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This is what a pandemic looks like: Visual framing of COVID-19 on search engines

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arxiv 2209.11120 v1 pith:QJMRKL2S submitted 2022-09-22 cs.IR

classification cs.IR
keywords searchenginescovid-19visualauditconsequencesimageinformation
verification ladder T0 review T1 audit T2 compute T3 formal
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In today's high-choice media environment, search engines play an integral role in informing individuals and societies about the latest events. The importance of search algorithms is even higher at the time of crisis, when users search for information to understand the causes and the consequences of the current situation and decide on their course of action. In our paper, we conduct a comparative audit of how different search engines prioritize visual information related to COVID-19 and what consequences it has for the representation of the pandemic. Using a virtual agent-based audit approach, we examine image search results for the term "coronavirus" in English, Russian and Chinese on five major search engines: Google, Yandex, Bing, Yahoo, and DuckDuckGo. Specifically, we focus on how image search results relate to generic news frames (e.g., the attribution of responsibility, human interest, and economics) used in relation to COVID-19 and how their visual composition varies between the search engines.

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