跨社交媒体舆情关键节点识别方法及其实证研究

Methodology and Empirical Research to Identify Key Nodes of Public Opinion Across Social Media

[目的/意义]结合超网络理论识别跨社交媒体舆情传播中的关键节点,对相关部门监管网络舆情、保障网络信息安全具有实践意义。[方法/过程]研究工作选取特定的网络舆情事件,利用跨社交媒体同一用户算法识别出参与跨社交媒体舆情传播的信息用户。以超网络理论为理论基础,对跨社交媒体舆情传播中的各子网进行建模,融合自然语言处理、主题挖掘、情感分析等方法,挖掘跨社交媒体舆情传播过程中的关键节点。[结果/结论]研究发现,本研究提出的跨社交媒体舆情关键节点识别方法,能够从不同视角识别与解读跨社交媒体舆情传播过程中的关键节点,从而更好地描述跨社交媒体舆情的传播过程与特点,为跨社交媒体舆情传播的研究提供了新的研究方法与思路。

[Purpose/Significance]Combining the theory of super network to identify key nodes in cross-social media public opinion dissemination has practical implications for relevant departments to regulate online public opinion and ensure network information security.[Method/Process]The research selected specific online public opinion events and used the same user algorithm across social media to identify information users participating in cross-social media public opinion dissemination.Based on super network theory,various subnets in cross-social media public opinion communication were modelled,and methods such as natural language processing,topic mining and sentiment analysis were integrated to explore key nodes in the process of cross-social media public opinion communication.[Result/Conclusion]Research found that the cross-social media public opinion key node identification method proposed in this study can identify and interpret key nodes in the process of cross-social media public opinion dissemination from different perspectives,thereby better describing the dissemination process and characteristics of cross-social media public opinion,and providing new research methods and ideas for the study of cross-social media public opinion dissemination.