LAUSR

In social topics, the study of rumor propagation mechanisms is essential to master social behavior. In this paper, aiming to explore the adversarial game relationship between rumor and anti-rumor in the propagation process and considering the sparse of real and effective data in the process of rumor propagation, we propose a rumor propagation model. First, considering the sparse data samples of effective cross-countermeasures in the process of spreading rumor and anti-rumor, a model of unsupervised GAN is used to enhance homomorphism data in the sample space. Second, aiming at the symbiotic and antagonistic game relationship between rumor and anti-rumor, evolutionary game theory is introduced. The internal and external factors that affect user behavior within rumor propagation are comprehensively considered, and a quantitative rumor-refutation mutual influence model is proposed. Finally, considering the dynamic time limit of rumor and anti-rumor propagation life cycle, we herein propose a simple prediction method of rumor topic group behavior based on a dynamic iteration mechanism. Experiments show that our method gets 9%-29% precision gains over the current methods on different datasets.