Immunization strategies for false information spreading on signed social networks

With high-speed communication and information sharing in social networks, the effective immunity to specific false information would markedly reduce the loss brought by the spreading of false information. To date, most studies only focus on the immunity of positive relationships for information spreading between individuals. However, negative relationships also exist in social networks and might have a strong influence on information spreading. In this study, three strategies of structural immunization and a heuristic strategy are proposed for signed social networks with both positive and negative relationships, which can effectively control the spread of false information by the users with opposing attitudes. After selecting the information spreading model suitable for signed networks, the influence of structural immunization strategies on spreading ranges is explored and shows different phase transitions which indicate that both positive and negative edges play a significant role in immune processes. Then, the results of two evaluation indices showed that the three proposed strategies had better immunity than the state-of-the-art approaches. In addition, to decrease algorithm complexity and achieve better performance, the results of the proposed structural strategies are selected to be the initial values of a heuristic strategy driven by a genetic algorithm. This study contributes to a deeper understanding of the role of negative relationships in information immunity and promotes the application of signed networks in information spreading and control.