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在在线协作环境中理解和应对极端主义:数据驱动建模

Understanding and coping with extremism in an online collaborative environment: A data-driven modeling.

作者信息

Rudas Csilla, Surányi Olivér, Yasseri Taha, Török János

机构信息

Institute of Physics, Budapest University of Technology and Economics, Budapest, Hungary.

Institute of Physics, Eötvös Loránd University, Budapest, Hungary.

出版信息

PLoS One. 2017 Mar 21;12(3):e0173561. doi: 10.1371/journal.pone.0173561. eCollection 2017.

Abstract

The Internet has provided us with great opportunities for large scale collaborative public good projects. Wikipedia is a predominant example of such projects where conflicts emerge and get resolved through bottom-up mechanisms leading to the emergence of the largest encyclopedia in human history. Disaccord arises whenever editors with different opinions try to produce an article reflecting a consensual view. The debates are mainly heated by editors with extreme views. Using a model of common value production, we show that the consensus can only be reached if groups with extreme views can actively take part in the discussion and if their views are also represented in the common outcome, at least temporarily. We show that banning problematic editors mostly hinders the consensus as it delays discussion and thus the whole consensus building process. To validate the model, relevant quantities are measured both in simulations and Wikipedia, which show satisfactory agreement. We also consider the role of direct communication between editors both in the model and in Wikipedia data (by analyzing the Wikipedia talk pages). While the model suggests that in certain conditions there is an optimal rate of "talking" vs "editing", it correctly predicts that in the current settings of Wikipedia, more activity in talk pages is associated with more controversy.

摘要

互联网为我们开展大规模协作性公益项目提供了巨大机遇。维基百科就是这类项目的一个典型例子,在这个项目中,冲突会出现,并通过自下而上的机制得到解决,最终形成了人类历史上最大的百科全书。每当持有不同意见的编辑试图撰写一篇反映共识观点的文章时,分歧就会产生。辩论主要由持有极端观点的编辑激化。通过一个共同价值生成模型,我们表明,只有当持有极端观点的群体能够积极参与讨论,并且他们的观点至少在短期内也能体现在共同成果中时,才能达成共识。我们表明,封禁有问题的编辑大多会阻碍共识的达成,因为这会延迟讨论,进而阻碍整个共识形成过程。为了验证该模型,我们在模拟和维基百科中都对相关量进行了测量,结果显示出令人满意的一致性。我们还在模型和维基百科数据中(通过分析维基百科的讨论页面)考虑了编辑之间直接沟通的作用。虽然模型表明在某些条件下存在“讨论”与“编辑”的最佳比例,但它正确地预测出,在维基百科当前的设置下,讨论页面上更多的活动与更多的争议相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8be0/5360246/8eb027246dab/pone.0173561.g001.jpg

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