Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics
October 27, 2020 Β· Declared Dead Β· π SIGKDD Explorations
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Authors
Tim Draws, Nava Tintarev, Ujwal Gadiraju, Alessandro Bozzon, Benjamin Timmermans
arXiv ID
2010.14531
Category
cs.IR: Information Retrieval
Citations
34
Venue
SIGKDD Explorations
Last Checked
4 months ago
Abstract
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 ground work for future research to measure and assess viewpoint diversity in real search result rankings.
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