Simulation-based evaluation of a crowdsourced expert peer review system

I. Lendák
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引用次数: 2

Abstract

The primary goal of this paper is to propose and simulate crowdsourcing-based solutions which might optimize the scientific peer review system. More specifically, a global reviewer database and gamification techniques will be proposed with the goal of obtaining more high-quality reviews for papers received by journals. The proposed modifications were assessed in a multi-agent simulation environment, in which the members of the reviewer crowd were modeled as agents. Our simulation-based evaluations implemented in the MASON multi-agent environment showed that the introduction of the above improvements would allow editors to find the most suitable and responsive reviewers, as well as to lower the number of scientific papers which do not receive enough reviews.
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基于仿真的众包专家同行评议系统评估
本文的主要目标是提出并模拟基于众包的解决方案,以优化科学同行评审系统。更具体地说,将提出一个全球审稿人数据库和游戏化技术,目的是为期刊收到的论文获得更多高质量的审稿。在一个多智能体仿真环境中对提出的修改进行评估,其中审稿人群体的成员被建模为智能体。我们在MASON多智能体环境中实施的基于模拟的评估表明,上述改进的引入将使编辑能够找到最合适和最敏感的审稿人,并减少没有得到足够审稿的科学论文的数量。
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