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在线社交网络上传播信息的动态

Fanhui Meng¹, Jiarong Xie^2,3,4, Jiachen Sun⁴

¹School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China.

Proceedings of the National Academy of Sciences of the United States of America

|January 23, 2025

概括

在社交媒体上传播的信息是由社会强化和削弱效应驱动的. 一个新的方程解释了这些复杂的动态跨平台,如微信,微博和推特.

科学领域:

社会科学社会科学社会科学
网络科学网络科学
计算社会科学计算社会科学

背景情况:

由于用户行为和信息的多样化,社交媒体平台表现出复杂的信息传播动态.
现有的信息传播模型往往是矛盾的,无法捕捉完整的画面.

研究的目的:

揭示一个统一的机制,管理在社交媒体上传播的信息.
开发一个简洁的模型,准确地描述大规模信息扩散轨迹.
解决争议并解释以前在社交媒体信息传播中观察到的现象.

主要方法:

分析来自主要社交媒体平台 (微信,微博,推特) 的大规模数据,覆盖74.5亿用户.
确定社会强化和社会削弱效应之间的相互作用,作为核心传播机制.
开发和验证一个简洁的数学方程来建模扩散动态.

主要成果:

一个无处不在的机制,由社会强化和削弱驱动,被确定为信息传播的主要因素.
一个单一的,简洁的方程被提出并被证明可以准确地建模各种不同的经验传播轨迹.
这项研究解释了以前有争议的说法和社交媒体传播中观察到的现象.
高度集群的社交网络促进了快速,高频的信息爆发,每次爆发的覆盖范围有限.

结论:

社会强化和削弱的相互作用为社交媒体信息传播提供了统一的解释.
拟议的方程为理解和预测信息扩散的规模提供了一个强大的工具.
聚类社交网络结构增强了社交媒体对多样化和快速信息传播的能力,支持其生态发展.

关键词:

信息的传播和传播.社交媒体社交媒体扩散动态的传播动态

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