Understanding How Algorithmic and Cognitive Biases in Web Search Affect User Attitudes on Debated Topics

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Abstract

Web search increasingly provides a platform for users to seek advice on important personal decisions [6] but may be biased in several different ways [1]. One result of such biases is the search engine manipulation effect (SEME): when a list of search results relates to a debated topic (e.g., veganism) and promotes documents pertaining to a particular viewpoint (e.g., by ranking them higher), users tend to adopt this advantaged viewpoint [5]. However, the detection and mitigation of SEME are complicated by the current lack of empirical understanding of its underlying mechanisms. This dissertation aims to investigate which (and to what degree) algorithmic and cognitive biases play a role in SEME concerning debated topics.
Original languageEnglish
Title of host publicationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery (ACM)
Pages2709-2709
Number of pages1
DOIs
Publication statusPublished - 2021
Event44th International ACM SIGIR Conference on Research and Development in Information Retrieval - Online, Monteal, Canada
Duration: 11 Jul 202115 Jul 2021
https://sigir.org/sigir2021/

Publication series

NameSIGIR '21

Conference

Conference44th International ACM SIGIR Conference on Research and Development in Information Retrieval
Abbreviated titleSIGIR 2021
CountryCanada
CityMonteal
Period11/07/2115/07/21
Internet address

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