Abstract

Rumors and misleading information propagation is one of the open problems in Online Social Networks (OSN) that haven’t mature solutions till now. In this paper, we propose a Colored Petri Net(CPN) model for detecting and blocking misleading information propagation in OSNs. We experimentally simulated and evaluated the effectiveness of our proposed model on dataset of 1003-newsworthy tweets under the trending topic (#ISIS) in Twitter social network. According to Precision, Recall, and Accuracy metrics, our obtained results cleared outperforming in detecting misleading newsworthy tweets compared with other mechanisms in the literature. In addition, verifying the Reachability property of our CPN model proved that detecting and blocking misleading tweets are reachable states according to the firing life-cycle of tokens.

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