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A sock puppet detection algorithm on virtual spaces

机译：虚拟空间上的袜子木偶检测算法

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摘要

On virtual spaces, some individuals use multiple usernames or copycat/forge other users (usually called "sock puppet") to communicate with others. Those sock puppets are fake identities through which members of Internet community praise or create the illusion of support for the product or one's work, pretending to be a different person. A fundamental problem is how to identify these sock puppets. In this paper, we propose a sock puppet detection algorithm which combines authorship-identification techniques and link analysis. Firstly, we propose an interesting social network model in which links between two IDs are built if they have similar attitudes to most topics that both of them participate in; then, the edges are pruned according a hypothesis test, which consider the impact of their writing styles; finally, the link-based community detection for pruned network is performed. Compared to traditional methods, our approach has three advantages: (1) it conforms to the practical meanings of sock puppet community; (2) it can be applied in online situation; (3) it increases the efficiency of link analysis. In the experimental work, we evaluate our method using real datasets and compared our approach with several previous methods; the results have proved above advantages.
机译：在虚拟空间上，某些人使用多个用户名或模仿/伪造其他用户（通常称为“袜子木偶”）与他人通信。这些袜子木偶是伪造的身份，Internet社区成员通过它们伪装成不同的人来赞扬或创建对产品或工作的支持的幻觉。一个基本问题是如何识别这些袜子木偶。本文提出了一种结合作者身份识别技术和链接分析的袜子木偶检测算法。首先，我们提出了一个有趣的社交网络模型，其中，如果两个ID对他们都参与的大多数主题具有相似的态度，则可以建立两个ID之间的链接；然后根据假设检验修剪边缘，考虑到书写风格的影响。最后，对修剪后的网络进行基于链接的社区检测。与传统方法相比，我们的方法具有三个优点：（1）符合袜子木偶社区的实际含义； （2）可以在线使用； （3）提高了链接分析的效率。在实验工作中，我们使用真实数据集评估我们的方法，并将我们的方法与以前的几种方法进行比较；结果证明了上述优点。

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