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Detecting Misinformation in Social Networks Using Provenance Data

机译:使用来源数据检测社交网络中的错误信息

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The credibility of information in social networks has attracted a lot of interest due to its important role in spreading information. We argue that the quality of information or objects created in social networks can be analyzed by using their provenance data. In this paper, we propose an algorithm that assesses the credibility of information on social networks to detect the propagation of fake or malicious information. To test the usability of the proposed algorithm, we introduce a prototype implementation and discuss it in detail. We test the prototype software on a large-scale synthetic social provenance dataset. The initial results are promising.
机译:社交网络中信息的可信度由于其在传播信息中的重要作用而引起了人们的极大兴趣。我们认为,社交网络中创建的信息或对象的质量可以通过使用其来源数据进行分析。在本文中,我们提出了一种算法,该算法评估社交网络上信息的可信度以检测伪造或恶意信息的传播。为了测试所提出算法的可用性,我们介绍了一个原型实现并对其进行了详细讨论。我们在大规模的综合社会来源数据集上测试了原型软件。初步结果令人鼓舞。

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