Title
Viewpoint Diversity in Search Results
Author
Draws, T.A. (TU Delft Web Information Systems) 
Roy, N. (TU Delft Web Information Systems)
Inel, Oana (University of Zürich)
Rieger, A. (TU Delft Web Information Systems)
Hada, Rishav (Microsoft Research)
Yalcin, Mehmet Orcun (Independent Researcher)
Timmermans, Benjamin (IBM Benelux)
Tintarev, N. (Universiteit Maastricht)
Contributor
Kamps, Jaap (editor)
Goeuriot, Lorraine (editor)
Crestani, Fabio (editor)
Maistro, Maria (editor)
Joho, Hideo (editor)
Davis, Brian (editor)
Gurrin, Cathal (editor)
Caputo, Annalina (editor)
Kruschwitz, Udo (editor)
Date
2023
Abstract
Adverse phenomena such as the search engine manipulation effect (SEME), where web search users change their attitude on a topic following whatever most highly-ranked search results promote, represent crucial challenges for research and industry. However, the current lack of automatic methods to comprehensively measure or increase viewpoint diversity in search results complicates the understanding and mitigation of such effects. This paper proposes a viewpoint bias metric that evaluates the divergence from a pre-defined scenario of ideal viewpoint diversity considering two essential viewpoint dimensions (i.e., stance and logic of evaluation). In a case study, we apply this metric to actual search results and find considerable viewpoint bias in search results across queries, topics, and search engines that could lead to adverse effects such as SEME. We subsequently demonstrate that viewpoint diversity in search results can be dramatically increased using existing diversification algorithms. The methods proposed in this paper can assist researchers and practitioners in evaluating and improving viewpoint diversity in search results.
Subject
Bias
Evaluation
Metric
Search results
Viewpoint diversity
To reference this document use:
http://resolver.tudelft.nl/uuid:38d694f2-52a3-4a00-88ea-02e09c721708
DOI
https://doi.org/10.1007/978-3-031-28244-7_18
Publisher
Springer, Cham
Embargo date
2023-09-17
ISBN
978-3-031-28243-0
Source
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings
Event
45th European Conference on Information Retrieval, ECIR 2023, 2023-04-02 → 2023-04-06, Dublin, Ireland
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 0302-9743, 13980
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2023 T.A. Draws, N. Roy, Oana Inel, A. Rieger, Rishav Hada, Mehmet Orcun Yalcin, Benjamin Timmermans, N. Tintarev