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PurposeIn social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.Design/methodology/approachWe collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.FindingsOfficial media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.Originality/valueThis study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.
PurposeIn social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.Design/methodology/approachWe collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.FindingsOfficial media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.Originality/valueThis study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.
Network public opinion is the reflection of social public opinion on the internet and an important part of social public opinion. There are various forms of network public opinion, including WeChat, Weibo, Twitter, etc., and the comments and interactions on these multiple platforms constitute the rich content of network public opinion. Real-time understanding of network public opinion propagation helps to grasp public feedback and emotions. When a public opinion crisis occurs, adopting effective control methods can quickly respond to and handle social hot events, avoid misunderstandings and the expansion of contradictions, and help maintain social harmony and stability. To address this problem, we propose a public opinion propagation model based on DI-SCIR for two-layer coupled social network. A strong coupled inter-layer connection method based on LBRank is proposed to establish a practical two-layer coupled social network. Theoretical analysis is conducted on the impact of different factors in the model on public opinion dissemination of coupled social network. A control method of direct immune SCIR is designed, which intervenes with real-time online users during the spreading of public opinion. This can guide public opinion to spread in a favorable direction. The simulation results show that the constructed public opinion propagation model for two-layer social network can better reflect the spreading of public opinion in real life. The public opinion control method can quickly guide and intervene in the spread of public opinion and reduce the impact of negative public opinion.
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