Aggregating partial, local evaluations to achieve global ranking
Disordered Systems and Neural Networks
2015-06-24 v1
Abstract
We analyze some voting models mimicking online evaluation systems intended to reduce the information overload. The minimum number of operations needed for a system to be effective is analytically estimated. When herding effects are present, linear preferential attachment marks a transition between trustful and biased reputations.
Cite
@article{arxiv.cond-mat/0409020,
title = {Aggregating partial, local evaluations to achieve global ranking},
author = {Paolo Laureti and Lionel Moret and Yi-Cheng Zhang},
journal= {arXiv preprint arXiv:cond-mat/0409020},
year = {2015}
}
Comments
9 pages, 5 figures, accepted for publication in Physica A