Is Approval Voting Optimal Given Approval Votes?
Abstract
Some crowdsourcing platforms ask workers to express their opinions by approving a set of k good alternatives. It seems that the only reasonable way to aggregate these k-approval votes is the approval voting rule, which simply counts the number of times each alternative was approved. We challenge this assertion by proposing a probabilistic framework of noisy voting, and asking whether approval voting yields an alternative that is most likely to be the best alternative, given k-approval votes. While the answer is generally positive, our theoretical and empirical results call attention to situations where approval voting is suboptimal.
Cite
Text
Procaccia and Shah. "Is Approval Voting Optimal Given Approval Votes?." Neural Information Processing Systems, 2015.Markdown
[Procaccia and Shah. "Is Approval Voting Optimal Given Approval Votes?." Neural Information Processing Systems, 2015.](https://mlanthology.org/neurips/2015/procaccia2015neurips-approval/)BibTeX
@inproceedings{procaccia2015neurips-approval,
title = {{Is Approval Voting Optimal Given Approval Votes?}},
author = {Procaccia, Ariel D and Shah, Nisarg},
booktitle = {Neural Information Processing Systems},
year = {2015},
pages = {1801-1809},
url = {https://mlanthology.org/neurips/2015/procaccia2015neurips-approval/}
}