Aggregating partial, local evaluations to achieve global ranking
Paolo Laureti, Lionel Moret, Yi-Cheng Zhang
TL;DR
This paper examines voting models for online evaluation systems, estimating the minimum operations needed for effectiveness and analyzing how herding effects influence reputation trustworthiness.
Contribution
It provides an analytical estimate of the minimum operations for effective online evaluation systems and explores the impact of herding effects on reputation bias.
Findings
Estimated the minimum operations for system effectiveness
Identified a transition point influenced by herding effects
Analyzed the impact of linear preferential attachment on reputation trust
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.
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