Optimal Number of Choices in Rating Contexts
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Proceedings of the NIPS 2016 Workshop on Imperfect Decision Makers, PMLR 58:6174, 2017.
Abstract
In many settings people must give numerical scores to
entities from a small discrete set. For instance, rating physical
attractiveness from 1–5 on dating sites, or papers from 1–10
for conference reviewing. We study the problem of understanding
when using a different number of options is optimal. For concreteness
we assume the true underlying scores are integers from 1–100.
We consider the case when scores are uniform random and Gaussian.
While in theory for this setting it would be optimal to use all 100
options, in practice this is prohibitive, and it is preferable to
utilize a smaller number of options due to humans’ cognitive limitations.
Our results suggest that using a smaller number of options than is typical
could be optimal in certain situations. This would have many potential
applications, as settings requiring entities to be ranked by humans are ubiquitous.
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