User Information Collection of Weibo Network Public Opinion under Python

Although the network environment is gradually improving, the virtual nature of the network is still the samefact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studiedby using Python technology. Specifically, the 2019 “Ethiopian air crash” event was taken as the researchsubject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayesclassifier. The Weibo network public opinion user identity graph model under the “Ethiopian air crash” on June20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easilyinfluenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinionusers have an influence on other types of public opinion users. That is to say, in the network public opinionspace of the “Ethiopian air crash,” media public opinion users play an important role in the dissemination ofnetwork public opinion information. This research can lay a foundation for the classification and identificationof user identity information types under different public opinion life cycles. Future research can start from thesupervision of public opinion and the type of user identity to improve the scientific management and control ofuser information dissemination through Weibo network public opinion. KCI Citation Count: 0