The continuous breeding and rapid spread of rumors in social networks poses a severe challenge to the effective utilization and scientific management of social media. Therefore, it is of great theoretical significance and application value to study the decision-making behavior of users in rumors spread in social networks and to reveal the rumor transmission rules. Based on the Ising model, this paper constructs a social network rumor propagation dynamics model and then reveals the rumor transmission rules. In the model, the Monte Carlo method is used to simulate the interaction between the user’s self-identity attribute (micropart), the user-user interaction (the middle part), and the social environment’s influence (the macroscopic part) to study user decision behavior of rumor spread in a social network system. The results show that, in the rumor propagation system, von Neumann entropy can quantify well the phase transition of the system and is consistent with the phase transition information obtained by measuring the spontaneous magnetization and magnetic susceptibility of the system. In addition, the introduction of the self-identity characteristics of individual users into the Ising model has greatly changed the users’ decision-making behavior of rumor spreading and changed the internal structure of the system, thus changing the type of phase transition. As the degree of self-identification increases, the need for lower temperatures can change the orderly state of the system, and user behavior changes more rapidly. For the rumor transmission system, the state of close order is conducive to the blocking of rumors, thus maintaining social stability.
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