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

Conference Paper (2021)
Author(s)

T.A. Draws (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Web Information Systems
DOI related publication
https://doi.org/10.1145/3404835.3463273 Final published version
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Publication Year
2021
Language
English
Research Group
Web Information Systems
Pages (from-to)
2709-2709
Event
44th International ACM SIGIR Conference on Research and Development in Information Retrieval (2021-07-11 - 2021-07-15), Online, Monteal, Canada
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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.

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