社交行为扩散、创新产品推广和大规模谣言传播等现象大量存在于现实社会中，这些社会传播往往相互作用、共同演化，进而形成多个耦合社会传播。然而，多个耦合社会传播在社交网络中的演化机制，及其所受社交网络结构的影响尚待系统研究。鉴于此，本项目致力于研究以下内容。首先，基于网络科学理论和时间序列分析方法，从真实的耦合社会传播数据中挖掘其演化机制和规律。然后，基于实证分析中所得到的演化机制，提出社交网络上的多个耦合社会传播模型。最后，针对不同的演化机制和社交网络结构，提出准确的理论方法来定量刻画传播动力学，进一步研究不同演化机制和社交网络结构对多个耦合社会传播的最终传播范围、爆发阈值和临界现象的影响。本项目采用实证分析与理论研究相结合的方法，保证项目的合理性和可行性。预期研究成果有助于更好地理解真实社交网络中的多个社会传播现象，为舆情预警与控制、产品营销和网络空间安全维护提供必要的理论支撑和决策依据。

Social behavior diffusion, innovation products popularizing and large-scale rumor spreading widely exist in real social system, those social contagions always interact with each other and coevolution, and further shapes the multiple coupled social contagions. Nevertheless, the evolution mechanisms of multiple social contagions on social networks, and the effects from network structures have not been systematically investigated. Therefore, this project focuses on studying the following aspects. First, based on the theory of network science and time series analysis, we investigate the evolution mechanisms and explore the laws from real data of multiple social contagions. Then, proposing multiple social contagion models in social networks based on the concluded evolution mechanisms from real data analysis. Finally, for different evolution mechanisms and topology structures of social networks, develop accurate theoretical approaches to describe the spreading dynamics, and further investigate the effects of evolution mechanisms and topology structures on the final outbreak size, outbreak threshold and critical behaviors of multiple social contagions. The project uses an approach combing both real data analysis and theoretical investigations, which ensures its rationality and feasibility. The expected results will help us to obtain a better understanding about real multiple social contagion phenomena in social networks, and provide theoretical supports and decision-making references for warning and containing of public sentiment, product marketing and maintaining cybersecurity.