Zhao Jianbo, Liu Huailiang, Dong Haiping, Zhang Weili, Xin Jige, Zhou Xuan, Wang Zhen, Zhang Xiaojin, Ren Xinyuan, Zhang Shanzhuang
Department of Economics & Management, Xidian University, 266 Xifeng Road, Xi'an, 710071, Shaanxi, China.
Department of Electronic Engineering, Xidian University, 266 Xifeng Road, Xi'an, 710071, Shaanxi, China.
Heliyon. 2024 Apr 22;10(9):e29995. doi: 10.1016/j.heliyon.2024.e29995. eCollection 2024 May 15.
Rumor governance is an important guarantee for social stability and public safety. Based on the life cycle and crisis cycle model, this paper conducts a synergistic analysis of China's rumor governance policies and regulations and the core scientific research literature on rumor governance in WOS and CNKI. In this paper, we use the TF-IDF algorithm to count the word frequencies of 326 policy and regulation texts, the Jieba-RoBERTa-Kmeans model to cluster high-frequency keywords, and CiteSpace software and the LLR clustering algorithm are utilized to extract and cluster keywords from 391 documents in the WOS database and from 703 documents in the CNKI database. Based on the synergistic analysis of the life cycle model, it is found that the research on policies and regulations precedes the research on literature, and both are in the period of refinement.Based on the synergistic analysis using the co-occurrence comparison of subject terms in the crisis cycle model, it is found that there is a lack of research in the stages of prevention, monitoring, and governance, and this paper proposes the systematic governance mechanism and strategy for crisis resolution that conforms to the trend of life cycle evolution and is synergistic with policy and literature. This study has only selected Chinese policies and regulations, and the proposed governance strategies have not yet been verified in practice; future research can expand the scope and depth of the study and conduct empirical research and pilot projects.
谣言治理是社会稳定和公共安全的重要保障。基于生命周期和危机周期模型，本文对中国谣言治理政策法规与WOS和CNKI中谣言治理核心科研文献进行协同分析。本文运用TF-IDF算法统计326篇政策法规文本的词频，采用结巴-罗伯塔-聚类算法对高频关键词进行聚类，并利用CiteSpace软件和对数似然率聚类算法从WOS数据库中的391篇文献以及CNKI数据库中的703篇文献中提取并聚类关键词。基于生命周期模型的协同分析发现，政策法规研究先于文献研究，二者均处于细化阶段。基于危机周期模型中主题词共现比较的协同分析发现，预防、监测和治理阶段缺乏研究，本文提出符合生命周期演变趋势且与政策和文献协同的危机解决系统治理机制和策略。本研究仅选取了中国的政策法规，所提出的治理策略尚未经过实践验证；未来研究可扩大研究范围和深度，并开展实证研究和试点项目。
