Research On User Participation In Public Opinion Topics Under Public Emergencies

Sudden public events have attracted people’s attention due to their suddenness,serious harm,and other characteristics.They have also sparked a wave of user participation in discussions on social media platforms.With the increasing level of discussion about events,related events will generate corresponding event topics,and Weibo Topics have become one of the important carriers of user participation.Super Topics is a network communication space developed by Sina-Weibo by combining Weibo Topics with community attributes.It has the characteristics of stronger information transmission,higher information utility,and more frequent user interaction.Through various interactive methods such as initiating topics,creating Super Topics,and participating in topic discussions on Sina-Weibo,users can directly participate in the dissemination of information related to public emergencies.More and more users seek or provide assistance by participating in posting or commenting on Weibo topics or Super Topics,and the related public opinion formed has also promoted the development of public emergencies.Studying the user’s participation behavior in sudden public events can facilitate the effective transmission of information during critical times,enhance the attention and improvement of government departments to the event,and help the social media platform develop in a more standardized and healthy manner.This research uses Python to obtain the text content and data information of rainstorm Super Topics platform of Sina-Weibo.First,the text content is classified and coded through content analysis to explore the type of social support in Super Topics.Then,through statistical analysis,summarize the basic data information of users’ first posting to measure their posting experience.Finally,a binary logistic regression model is constructed to analyze whether the experience gained by the first post of Super Topics users will affect their subsequent postings,so as to explore the influencing factors that affect users’ continued posting.Research has found that the information within a hypertext is mainly divided into four types of social support information: information support,emotional support,reality support,and diffusion support;The results of logistic regression indicate that the matching degree of social support,the number of posts forwarded,the number of replies received,the number of likes on posts,and the length of post text will have an impact on users’ continued posting behavior,while the average length of replies received will not have an impact.Based on the above research results,countermeasures and suggestions are proposed for the healthy and sustainable development of social media platforms,providing reference for government departments to better promote the progress of public emergencies,and thus enriching relevant research on user participation behavior in public emergencies.