Two-Stage Information Spreading Evolution on the Control Role of Announcements

IF 4.5 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

IEEE Transactions on Computational Social Systems Pub Date : 2024-03-12 DOI:10.1109/TCSS.2024.3367385

Jinhu Ren;Fuzhong Nian;Xiaochen Yang

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引用次数: 0

Abstract

Modern social media networks have become an important platform for information competition among countries, regions, companies, and other parties. This article utilizes the research method of spread dynamics to investigate the influence of the control role of announcements in social networks on the spreading process. This article distinguishes two spreading phases using the authentication intervention as a boundary: the unconfirmed spreading phase and the confirmed spreading phase. Based on the actual rules of spreading in online social networks, two kinds of verification results are defined: true information and false information. The two-stage information spreading dynamics model is developed to analyze the changes in spreading effects due to different validation results. The impact of the intervention time on the overall spread process is analyzed by combining important control factors such as response cost and time sensitivity. The validity of the model is verified by comparing the model simulation results with real cases and the adaptive capacity experiments. This work is analyzed and visualized from multiple perspectives, providing more quantitative results. The research content will provide a scientific basis for the intervention behavior of information management control by relevant departments or authorities.

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关于公告控制作用的两阶段信息传播演化

现代社交媒体网络已成为国家、地区、企业等各方信息竞争的重要平台。本文运用传播动力学的研究方法，探讨社交网络中公告的控制作用对传播过程的影响。本文以认证干预为界，将传播分为两个阶段：未确认传播阶段和已确认传播阶段。根据在线社交网络的实际传播规则，定义了两种验证结果：真实信息和虚假信息。建立两阶段信息传播动力学模型，分析不同验证结果导致的传播效果变化。结合响应成本和时间敏感性等重要控制因素，分析了干预时间对整个传播过程的影响。通过将模型模拟结果与实际案例和自适应能力实验进行比较，验证了模型的有效性。这项工作从多个角度进行分析和可视化，提供了更多量化结果。研究内容将为相关部门或权威机构的信息管理控制干预行为提供科学依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)

CiteScore

10.00

自引率

20.00%

发文量

316

期刊介绍： IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.

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