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.

Our beliefs about the world are generally not formed in isolation: the inherently social nature of human beings means that much of what we believe to know is based, at least in part, on information gained from others. Consequently, human knowledge and its acquisition cannot be fully understood by considering individuals alone. In this paper, we examine the belief dynamics in a group of networked participants engaged in a simple, factual estimation task. Specifically, we examine the extent to which participants revise their own judgments in light of others’ responses, and compare formal models of that process.