| Citation: | TANG Hongmei, TANG Wenzhong, LI Ruichen, et al. Classification of network public opinion propagation pattern based on variational reasoning[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(2): 209-216. doi: 10.13700/j.bh.1001-5965.2020.0538(in Chinese)
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With the rapid development of online social media, the analysis of the dissemination mode of public opinion information has become a research hotspot.Aiming at the problem of low classification accuracy of small sample data multi-path generation in the classification task of the network public opinion spreading pattern, the definition of the knowledge graph structure in the field of public opinion dissemination is proposed, builds a public opinion dissemination knowledge graph and public opinion dissemination analysis task data set based on Weibo data, uses the GraphDIVA model to classify public opinion propagation patterns, and conducts a 25-sample test experiment of public opinion propagation pattern classification in the self-built data set. The results show that, after 20 rounds of training, the classification accuracy rate of the model has increased from 76% to 89.4%. It can be seen that the GraphDIVA model has a better effect in reducing the number of training and improving the classification accuracy rate.
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