| As an important platform for the public to express public sentiment and public opinion,Weibo has attracted more and more attention.The Weibo platform has become one of the important carriers for the spread of online public opinion.In recent years,unexpected incidents have occurred frequently.Traditional media cannot meet the needs of public opinion.The publicity process and channels are also transferred to the Weibo platform.It is imperative to analyze the user behavior on the Weibo platform.After the emergencies,Weibo users quickly spread the incidents and carefully analyze the behavior of Weibo users during the information dissemination process,so as to actively and effectively control the behavior of Weibo users in emergencies,social stability and good public opinion.Guiding is important.The user's microblog characteristics are extracted from the real data,and the behavior influencing factors are correctly analyzed to predict the user behavior,and the purpose of effectively predicting and supervising emergencies is achieved.This article takes the "Changchun Longevity Vaccine" incident as an example to analyze the public sentiment propagation process of the whole emergency.Firstly,the reptile software is used to extract the original data of the event in Sina Weibo,and the microblog's attention,forwarding and comment functions are used as indicators.Analyze the follow-up behavior,forwarding behavior,and comment behavior of Weibo users.The purpose is to explore the intrinsic factors of user behavior in the network communication of emergencies.The four influencing factors of user participation,activity,attention and communication are the important factors to measure user behavior,and the non-predictive algorithm of machine learning is used.User behavior is predicted,and the behavior of Weibo users in emergencies is analyzed and analyzed.Finally,relevant suggestions are proposed for different types of users,in order to provide reference for future public opinion control of emergencies. |
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