Evolution of online public opinion based on chain of sub-events
The evolution analysis of the public opinion in emergency is the foundation for the risk prevention and control.An analysis framework for the evolution of the public opinion was proposes based on the event chain.Firstly,text mining technology was used to extract the main sub-events from the massive text stream,thereby reducing the public opinion content to the order of magnitude that can be manual interpretation and discrimination.Secondly,the word mover's distance was used to calculate the similarity of sub-events on two adjacent time slices,so that the event chain diagram could be constructed.The evolution analysis was carried out with the case of"Tesla spontaneous combustion in Shanghai".The relationship of topic shifting was built between sub-events at different stages of the evolution.Finally,it was verified by the robustness analysis that the method can reduce the problem of redundant information in short texts of microblogs and improve the accuracy of sub-event correlation.The research results provide decision support for the post-event review,the prediction and intervention of similar public opinion events,and the scientific evaluation of sub-events.
chain of sub-eventspublic opinion evolutiononline public opinionTesla spontaneously combustion
NETL
NSTL
万方数据
