Ranked Voting on Social Networks
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 2040-2045.
Abstract
Classic social choice theory assumes that votes are independent (but possibly conditioned on an underlying objective ground truth). This assumption is unrealistic in settings where the voters are connected via an underlying social network structure, as social interactions lead to correlated votes. We establish a general framework — based on random utility theory — for ranked voting on a social network with arbitrarily many alternatives (in contrast to previous work, which is restricted to two alternatives). We identify a family of voting rules which, without knowledge of the social network structure, are guaranteed to recover the ground truth with high probability in large networks, with respect to a wide range of models of correlation among input votes.
@inproceedings{ijcai2015p289,
title = {Ranked Voting on Social Networks},
author = {Procaccia, Ariel D. and Shah, Nisarg and Sodomka, Eric},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {2040--2045},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/289},
}
TY - CPAPER TI - Ranked Voting on Social Networks AU - Procaccia, Ariel D. AU - Shah, Nisarg AU - Sodomka, Eric T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 2040 EP - 2045 UR - https://ijcai.org/proceedings/2015/289 ER -Copied
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