Assessing viewpoint diversity in search results using ranking fairness metrics

Tim Draws*, Nava Tintarev, Ujwal Gadiraju

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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The way pages are ranked in search results influences whether the users of search engines are exposed to more homogeneous, or rather to more diverse viewpoints. However, this viewpoint diversity is not trivial to assess. In this paper, we use existing and novel ranking fairness metrics to evaluate viewpoint diversity in search result rankings. We conduct a controlled simulation study that shows how ranking fairness metrics can be used for viewpoint diversity, how their outcome should be interpreted, and which metric is most suitable depending on the situation. This paper lays out important groundwork for future research to measure and assess viewpoint diversity in real search result rankings.
Original languageEnglish
Pages (from-to)50-58
Number of pages9
JournalACM SIGKDD Explorations Newsletter
Issue number1
Publication statusPublished - 2021

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