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本文引用的文献

1
Behavioral experiments on biased voting in networks.网络中偏向性投票的行为实验。
Proc Natl Acad Sci U S A. 2009 Feb 3;106(5):1347-52. doi: 10.1073/pnas.0808147106. Epub 2009 Jan 23.
2
An experimental study of the coloring problem on human subject networks.关于人类主体网络中着色问题的实验研究。
Science. 2006 Aug 11;313(5788):824-7. doi: 10.1126/science.1127207.

网络着色与共识中的行为动态与影响。

Behavioral dynamics and influence in networked coloring and consensus.

机构信息

Computer and Information Science, University of Pennsylvania, Levine Hall, Philadelphia, PA, USA.

出版信息

Proc Natl Acad Sci U S A. 2010 Aug 24;107(34):14978-82. doi: 10.1073/pnas.1001280107. Epub 2010 Aug 9.

DOI:10.1073/pnas.1001280107
PMID:20696936
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2930545/
Abstract

We report on human-subject experiments on the problems of coloring (a social differentiation task) and consensus (a social agreement task) in a networked setting. Both tasks can be viewed as coordination games, and despite their cognitive similarity, we find that within a parameterized family of social networks, network structure elicits opposing behavioral effects in the two problems, with increased long-distance connectivity making consensus easier for subjects and coloring harder. We investigate the influence that subjects have on their network neighbors and the collective outcome, and find that it varies considerably, beyond what can be explained by network position alone. We also find strong correlations between influence and other features of individual subject behavior. In contrast to much of the recent research in network science, which often emphasizes network topology out of the context of any specific problem and places primacy on network position, our findings highlight the potential importance of the details of tasks and individuals in social networks.

摘要

我们报告了在网络环境下关于颜色(社会区分任务)和共识(社会一致任务)的人类主体实验。这两个任务都可以看作是协调博弈,尽管它们在认知上相似,但我们发现,在一个参数化的社交网络家族中,网络结构在两个问题中引发了相反的行为效应,即远距离连接使主体更容易达成共识,而使颜色更难。我们调查了主体对其网络邻居和集体结果的影响,并发现它变化很大,超出了仅通过网络位置可以解释的范围。我们还发现,影响力与个体主体行为的其他特征之间存在很强的相关性。与网络科学中许多经常强调网络拓扑结构而不考虑任何特定问题的背景并优先考虑网络位置的研究不同,我们的研究结果突出了社会网络中任务和个体的细节的潜在重要性。