Abstract
As one of the ways to reflect the views of the masses in modern society, online reviews have great value in public opinion research. The analysis of potential public opinion information from online reviews has a certain value for the government to clarify the next work direction. In this paper, the event evolution graph is designed to make COVID-19 network public opinion prediction. The causal relationship was extracted in the network reviews after the COVID-19 incident to build an event evolution graph of COVID-19 and predict the possibility of the occurrence of the derivative public opinion. The research results show the hot events and evolution direction of COVID-19 network public opinion in a clear way, and it can provide reference for the network regulatory department to implement intervention.
Foundation Items: The National Natural Science Foundation of China (No. 61572521), Engineering University of PAP Innovation Team Science Foundation (No. KYTD201805), The National Social Science Fund of China (No. 20XTQ007, 2020-SKJJ-B-019).
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Chen, X., Pan, F., Han, Y., Wu, R. (2021). Research on COVID-19 Internet Derived Public Opinions Prediction Based on the Event Evolution Graph. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2021. Communications in Computer and Information Science, vol 1452. Springer, Singapore. https://doi.org/10.1007/978-981-16-5943-0_4
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