Incentive Mechanisms for Crowdblocking Rumors in Mobile Social Networks

Mobile social networks (MSNs) have become an indispensable way for people to access information, express emotions, and communicate with each other. However, the advent and extensive use of MSNs has also created fertile soil for the breeding and rapid spread of rumors. Therefore, blocking the spread of rumors in MSNs has always been a hot topic in this field. With the idea of crowdsourcing, we propose a novel rumor control framework, called Crowdblocking, in which users can implement control schemes in a collaborative and distributed way, so that the rumors can be controlled more effectively. With the proposed framework, the main problem that arises is how to motivate more users to actively participate in rumor blocking activities. To this end, we design two effective incentive mechanisms in this paper. First, we propose an incentive mechanism based on the Stackelberg game for homogeneous control tasks. We theoretically analyze the Stackelberg equilibrium to maximize the utility of the network manager and users involved in blocking rumor tasks, and ensure that no user can improve its own utility by unilaterally changing the current strategy. Second, for heterogeneous control tasks, we design a real-time reverse auction incentive mechanism, which allows users to have more autonomy and freely customize their own plans to participate in control tasks. Also, we prove that the mechanism possesses the desired properties of task timeliness, computational efficiency, user rationality, manager profitability, and price truthfulness. Finally, we validate the efficiency of the proposed mechanisms through extensive simulation experiments on the real datasets.