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Measuring Quality, Reputation and Trust in Online Communities

机译:衡量在线社区的质量,声誉和信任

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In the Internet era the information overload and the challenge to detect quality content has raised the issue of how to rank both resources and users in online communities. In this paper we develop a general ranking method that can simultaneously evaluate users' reputation and objects' quality in an iterative procedure, and that exploits the trust relationships and social acquaintances of users as an additional source of information. We test our method on two real online communities, the EconoPhysics forum and the Last.fm music catalogue, and determine how different variants of the algorithm influence the resultant ranking. We show the benefits of considering trust relationships, and define the form of the algorithm better apt to common situations.
机译:在Internet时代,信息过载和检测高质量内容的挑战提出了如何对在线社区中的资源和用户进行排名的问题。在本文中,我们开发了一种通用的排名方法,该方法可以在迭代过程中同时评估用户的声誉和对象的质量,并利用用户的信任关系和社交关系作为其他信息来源。我们在两个实际的在线社区(EconoPhysics论坛和Last.fm音乐目录)上测试了我们的方法,并确定了算法的不同变体如何影响最终排名。我们展示了考虑信任关系的好处,并定义了更适合常见情况的算法形式。

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