Detecting Misinformation in Social Networks Using Provenance Data

Abstract

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.