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Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics

arXiv 2010.14531 ↗First posted 27 Oct 2020cs.IRcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Oct 2020.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 1; 2025: 5; 2026: 1.

11 papers.