Dynamic Online Networks Laboratory, George Washington University, Washington, DC, 20052, USA.
Physics Department, George Washington University, Washington, DC, 20052, USA.
Sci Rep. 2023 Sep 20;13(1):15640. doi: 10.1038/s41598-023-42893-6.
Why does online distrust (e.g., of medical expertise) continue to grow despite numerous mitigation efforts? We analyzed changing discourse within a Facebook ecosystem of approximately 100 million users who were focused pre-pandemic on vaccine (dis)trust. Post-pandemic, their discourse interconnected multiple non-vaccine topics and geographic scales within and across communities. This interconnection confers a unique, system-level (i.e., at the scale of the full network) resistance to mitigations targeting isolated topics or geographic scales-an approach many schemes take due to constrained funding. For example, focusing on local health issues but not national elections. Backed by numerical simulations, we propose counterintuitive solutions for more effective, scalable mitigation: utilize "glocal" messaging by blending (1) strategic topic combinations (e.g., messaging about specific diseases with climate change) and (2) geographic scales (e.g., combining local and national focuses).
尽管已经采取了许多缓解措施，但为什么网络不信任（例如，对医学专业知识的不信任）仍在持续增长？我们分析了一个拥有大约 1 亿用户的 Facebook 生态系统内不断变化的言论，这些用户在疫情前主要关注疫苗（不信任）。疫情后，他们的言论将多个非疫苗主题和地理尺度在社区内和跨社区相互关联。这种相互关联赋予了一种独特的、系统级的（即在整个网络规模上）对针对孤立主题或地理尺度的缓解措施的抵抗力——由于资金有限，许多方案都采用了这种方法。例如，专注于当地的健康问题，而不关注全国选举。我们的研究得到了数值模拟的支持，为更有效、更具可扩展性的缓解措施提出了反直觉的解决方案：利用“全球化本地化”信息传播，融合（1）战略主题组合（例如，将特定疾病与气候变化的信息相结合）和（2）地理尺度（例如，将本地和国家重点相结合）。
