School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, 632014, India.
Sci Rep. 2024 Aug 17;14(1):19100. doi: 10.1038/s41598-024-69657-0.
Online digital networks, including social networks, have significantly impacted individuals' personal and professional lives. Aside from exchanging news and topics of interest, digital networks play an essential role in the diffusion of information, which frequently significantly impacts worldwide societies. In this paper, we present a new mathematical epidemic model for digital networks that considers the sentiment of solitary misinformation in the networks and characteristics of human intelligence that play an important role in judging and spreading misinformation inside the networks. Our mathematical analysis has proved the existence and validity of the system in a real-time environment. Considering the real-world data, our simulation predicts how the misinformation could spread among different global communities and when an intervention mechanism should have to be carried out by the policyholders. Our simulation using the model proves that effective intervention mechanisms by isolating the fake news can effectively control the spread of misinformation among larger populations. The model can analyze the emotional and social intelligence of groups frequently subjected to disinformation and disseminating fake news.
在线数字网络，包括社交网络，已经极大地影响了个人的生活和工作。除了交流新闻和感兴趣的话题外，数字网络在信息传播中起着至关重要的作用，这些信息传播经常对全球社会产生重大影响。在本文中，我们提出了一个新的数字网络传染病模型，该模型考虑了网络中孤独错误信息的情绪以及人类智能的特征，这些特征在网络内部判断和传播错误信息方面发挥着重要作用。我们的数学分析已经证明了在实时环境下系统的存在和有效性。考虑到实际数据，我们的模拟预测了错误信息如何在不同的全球社区中传播，以及何时应该由政策制定者实施干预机制。我们使用模型的模拟证明了通过隔离假新闻的有效干预机制可以有效地控制错误信息在更大人群中的传播。该模型可以分析经常受到虚假信息和传播假新闻影响的群体的情绪和社会智能。
