Navigating the Thin Line: Examining User Behavior in Search to Detect Engagement and Backfire Effects

Federico Maria Cau*, Nava Tintarev

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Abstract

Opinionated users often seek information that aligns with their preexisting beliefs while dismissing contradictory evidence due to confirmation bias. This conduct hinders their ability to consider alternative stances when searching the web. Despite this, few studies have analyzed how the diversification of search results on disputed topics influences the search behavior of highly opinionated users. To this end, we present a preregistered user study (n = 257) investigating whether different levels (low and high) of bias metrics and search results presentation (with or without AI-predicted stances labels) can affect the stance diversity consumption and search behavior of opinionated users on three debated topics (i.e., atheism, intellectual property rights, and school uniforms). Our results show that exposing participants to (counter- attitudinally) biased search results increases their consumption of attitude-opposing content, but we also found that bias was associated with a trend toward overall fewer interactions within the search page. We also found that 19% of users interacted with queries and search pages but did not select any search results. When we removed these participants in a post-hoc analysis, we found that stance labels increased the diversity of stances consumed by users, particularly when the search results were biased. Our findings highlight the need for future research to explore distinct search scenario settings to gain insight into opinionated users’ behavior.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Proceedings
EditorsNazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis
PublisherSpringer Verlag
Pages403-419
Number of pages17
Volume14611 LNCS
ISBN (Print)9783031560651
DOIs
Publication statusPublished - 1 Jan 2024
Event46th European Conference on Information Retrieval 2024 - Glasgow, United Kingdom
Duration: 24 Mar 202428 Mar 2024
https://www.ecir2024.org/

Publication series

SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14611 LNCS
ISSN0302-9743

Conference

Conference46th European Conference on Information Retrieval 2024
Abbreviated titleECIR 2024
Country/TerritoryUnited Kingdom
CityGlasgow
Period24/03/2428/03/24
Internet address

Keywords

  • bias metrics
  • confirmation bias
  • search behavior

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