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AUTrust: A Practical Trust Measurement for Adjacent Users in Social Networks

机译:autrust:社交网络中相邻用户的实际信任测量

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摘要

Trust is the foundation of interpersonal relationship and interaction as in social networks as in real world. Previous researches about the trust between users mainly focus on nonadjacent users in social networks, where the trust between adjacent users is assumed to be known. However, in most social networks, the trust between adjacent users is unknown, that limits the applications of those nonadjacent users trust models. In this paper, we propose an adjacent users trust measurement model(AUTrust) and discuss how to construct a trust social network with AUTrust. The factors affecting trust between users could be classified into three dimensions: (i) similarity between users, (ii) familiarity between users, (iii) users' social reputation. The last two dimensions can be used to reflect asymmetry of trust between users. Then we discuss the methods of quantifying trust with these dimensions. Users' information that AUTrust needs can be collected with API provided by social networks, so the model can be widely applied to social networks. Finally, we evaluated the model on 10-million-level Ten cent Weibo dataset, and the experiment proves the practicability and universality of AUTrust model.
机译:信任是人际关系和互动的基础,就像在现实世界中的社交网络一样。以前关于用户信任的研究主要专注于社交网络中的非附带用户,其中假设已知相邻用户之间的信任。然而,在大多数社交网络中,相邻用户之间的信任未知,这限制了那些非公共用户信任模型的应用程序。在本文中,我们提出了一个相邻的用户信任测量模型(自动),并讨论如何通过自动构建信任社交网络。影响用户信任的因素可以分为三个维度:(i)用户之间的相似性,(ii)用户之间的熟悉程度,(iii)用户的社会声誉。最后两个维度可用于反映用户之间的信任的不对称性。然后我们讨论使用这些维度量化信任的方法。用户的信息可以通过社交网络提供的API收集自动需求的信息,因此该模型可以广泛应用于社交网络。最后,我们评估了1000万级十分微博数据集的模型,实验证明了自动模型的实用性和普遍性。

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