Rumor Remove Order Strategy on Social Networks

Abstract

Rumors are defined as widely spread talk with no reliable source to back it up. In modern society, the rumors are widely spreading on the social network. The spread of rumors poses great challenges for the society. A ”fake news” story can rile up your emotions and change your mood. Some rumors can even cause social panic and economic losses. As such, the influence of rumors can be far-reaching and long-lasting. Efficient and intelligent rumor control strategies are necessary to constrain the spread of rumors. Existing rumor control strategies are designed for controlling a single rumor. However, there are usually many rumors existing on social networks and only limited rumors can be removed at a time due to the limited detection capacity and CPU performance. Consequently, when dealing with multiple rumors, we should remove rumors in a certain order. We argue that the order of removing rumors matters as different rumors possess different properties, e.g., acceptance rate, propagation speed, etc. Unfortunately, to the best of our knowledge, there is no prior work on removing multiple rumors and the order of removing rumors. To this end, this paper proposes two novel rumor control strategies to remove the multiple rumors. We also extends the classical Susceptible Infected Recovered (SIR) model to simulate the dynamics of rumor propagation in a more practical manner. We evaluate the performance of strategies. The experiments show that our proposed rumor control strategies obviously outperform than benchmark strategy.