基于超级网络的公众意见反转认可
1College of Economics and Management, Nanjing Forestry University, Nanjing, People's Republic of China.
Big data
|August 22, 2025
概括
这项研究引入了一个超级网络模型来追踪紧急情况下的论变化. 该模型有效地识别了推动民意转变的关键因素,从而有助于危机管理.
科学领域:
- 社会网络分析
- 计算社会科学
- 公众论的动态
背景情况:
- 社交媒体加速了紧急信息的传播和论的转变.
- 在紧急情况下的意见转变会影响社会稳定和政府信任.
- 超级网络理论为分析复杂的多代理互动提供了一个框架.
研究的目的:
- 开发一种新的方法来识别紧急情况下的论转变.
- 使用超级网络方法分析论演变的动态.
- 提供应急响应和公众论监测的实际指导.
主要方法:
- 一个四层子网模型的构建:用户交互,事件演变,语义关联和情感传导网络.
- 网络结构特征的提取和跨层链接分析.
- 在2021年河南暴雨期间对洪兴埃尔克捐赠事件的案例研究分析.
主要成果:
- 提出的超级网络模型有效地确定了影响公众论转变的关键节点.
- 一个多指标协作识别系统可以快速检测意见转变的信号.
- 经验分析验证了模型在捕捉现实世界意见动态方面的能力.
结论:
- 超级网络模型为动态论分析提供了强有力的方法.
- 有效识别意见反转有助于及时和明智的紧急决策.
- 这项研究提供了在危机中管理论的理论和实践见解.
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