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Rank Aggregation and Belief Revision Dynamics

Abstract

In this paper we compare several popular rank aggregationmethods by accuracy of finding the true (correct) ranked list.Our research reveals that under most common circumstancessimple methods such as the average or majority actually tendto outperform computationally-intensive distance-based meth-ods. We then conduct a study to compare how actual peopleaggregate ranks in a group setting. Our finding is that individ-uals tend to adopt the group mean in a third of all revisions,making it the most popular strategy for belief revision.

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