Abstract:The diverse and complex trend of public opinion has long made it difficult to manage. Negative public opinion will intensify contradictions, bringing adverse effects to social stability. Then a method of public opinion deduction based on the event knowledge graph is proposed. The causal logic of the event is mined through the neural network, and the event knowledge graph is drawn after causal events are connected. Vectorized event nodes can merge into similar nodes to reduce map redundancy while enhancing map generalization. Besides, the evolution of target public opinion events can be predicted based on the deductive logic indicated in the event knowledge graph. With a public opinion event related to a natural disaster as an example, the experimental results prove that the proposed method can reliably predict the trend of the event, supporting public opinion supervision.