research-article

Enhancing credibility judgment of web search results

Authors:

Yusuke Yamamoto,

Katsumi TanakaAuthors Info & Claims

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1235 - 1244

https://doi.org/10.1145/1978942.1979126

Published: 07 May 2011 Publication History

Abstract

In this paper, we propose a system for helping users to judge the credibility of Web search results and to search for credible Web pages. Conventional Web search engines present only titles, snippets, and URLs for users, which give few clues to judge the credibility of Web search results. Moreover, ranking algorithms of the conventional Web search engines are often based on relevance and popularity of Web pages. Towards credibility-oriented Web search, our proposed system provides users with the following three functions: (1) calculation and visualization of several scores of Web search results on the main credibility aspects, (2) prediction of user's credibility judgment model through user's credibility feedback for Web search results, and (3) re-ranking of Web search results based on user's predicted credibility model. Experimental results suggest that our system enables users - in particular, users with knowledge about search topics - to find credible Web pages from a list of Web search results more efficiently than conventional Web search interfaces.

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Cited By

Bink MElsweiler D(2024)Balancing Act: Boosting Strategies for Informed Search on Controversial TopicsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638329(254-265)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638329
Bink MSchwarz SDraws TElsweiler D(2023)Investigating the Influence of Featured Snippets on User AttitudesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578323(211-220)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578323
Wang ADe Jesus Sanchez LWintner AZhu YMustafaraj E(2023)Assessing Google Search’s New Features in Supporting Credibility judgments of Unknown WebsitesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578277(303-307)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578277
Show More Cited By

Index Terms

Enhancing credibility judgment of web search results
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Information systems
  1. Information retrieval
  2. World Wide Web

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

May 2011

3530 pages

ISBN:9781450302289

DOI:10.1145/1978942

General Chair:
Desney Tan
Microsoft Research
,
Program Chairs:
Geraldine Fitzpatrick
Vienna University of Technology
,
Carl Gutwin
University of Saskatchewan
,
Bo Begole
PARC
,
Wendy A. Kellogg
IBM Research

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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New York, NY, United States

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Published: 07 May 2011

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CHI '11

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CHI '11: CHI Conference on Human Factors in Computing Systems

May 7 - 12, 2011

BC, Vancouver, Canada

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CHI '11 Paper Acceptance Rate 410 of 1,532 submissions, 27%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Bink MElsweiler D(2024)Balancing Act: Boosting Strategies for Informed Search on Controversial TopicsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638329(254-265)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638329
Bink MSchwarz SDraws TElsweiler D(2023)Investigating the Influence of Featured Snippets on User AttitudesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578323(211-220)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578323
Wang ADe Jesus Sanchez LWintner AZhu YMustafaraj E(2023)Assessing Google Search’s New Features in Supporting Credibility judgments of Unknown WebsitesProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578277(303-307)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578277
Kondo AAbe H(2023)Travel blogger credibility scoring method for recommendation system2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM56909.2023.10035643(1-4)Online publication date: 3-Jan-2023
https://doi.org/10.1109/IMCOM56909.2023.10035643
van Berkel NSarsenbayeva ZGoncalves J(2023)The methodology of studying fairness perceptions in Artificial IntelligenceInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2022.102954170:COnline publication date: 8-Feb-2023
https://dl.acm.org/doi/10.1016/j.ijhcs.2022.102954
Liao QSundar S(2022)Designing for Responsible Trust in AI Systems: A Communication PerspectiveProceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency10.1145/3531146.3533182(1257-1268)Online publication date: 21-Jun-2022
https://dl.acm.org/doi/10.1145/3531146.3533182
Bink MZimmerman SElsweiler DElsweiler DKruschwitz ULudwig B(2022)Featured Snippets and their Influence on Users’ Credibility JudgementsProceedings of the 2022 Conference on Human Information Interaction and Retrieval10.1145/3498366.3505766(113-122)Online publication date: 14-Mar-2022
https://dl.acm.org/doi/10.1145/3498366.3505766
Fernández-Pichel MLosada DPichel J(2022)A multistage retrieval system for health-related misinformation detectionEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105211115(105211)Online publication date: Oct-2022
https://doi.org/10.1016/j.engappai.2022.105211
Fernández-Pichel MLosada DPichel JElsweiler D(2021)Comparing Traditional and Neural Approaches for Detecting Health-Related MisinformationExperimental IR Meets Multilinguality, Multimodality, and Interaction10.1007/978-3-030-85251-1_7(78-90)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1007/978-3-030-85251-1_7
Fernández-Pichel MLosada DPichel JElsweiler D(2021)Reliability Prediction for Health-Related Content: A Replicability StudyAdvances in Information Retrieval10.1007/978-3-030-72240-1_4(47-61)Online publication date: 28-Mar-2021
https://dl.acm.org/doi/10.1007/978-3-030-72240-1_4
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