Information diffusion is a complex and dynamic process that involves the topological factor of social networks, and the geographical and psychological factors of individuals, etc. It has a wide range of applications, including online marketing, recommendation systems, and prevention of malware and rumours propagation. As dynamical models are in forms of difference, differential, partial differential, or stochastic differential equations, the corresponding mathematical tools, such as stability and bifurcation analysis, matrix analysis, perturbation theory, and fuzzy rules, can help us to understand the complex behaviours of the diffusion process.

Although lots of dynamical models describing the behaviours of information diffusion have been proposed, it is still a challenging interdisciplinary task to explain and predict the dynamics of the diffusion process in complex networks. Meanwhile, since there is an increasing interest in the study of how to control the diffusion of positive information, negative information, misinformation, and rumour, it is essential to study control models for information diffusion using hybrid control methods.

This Special Issue aims to provide both theoreticians and practitioners with a platform to disseminate their research on the modelling, analysis, and optimization of information diffusion over social networks. We encourage original related research papers from different disciplines ranging from computer science, physics, mathematics, to sociology. Furthermore, high-quality review articles describing the current state of the art are also invited.

Potential topics include but are not limited to the following:

• Recent developments in the area of information diffusion
• Deterministic/ stochastic model of information diffusion
• Data-centric model for information diffusion
• Numerical modeling approaches for information diffusion
• Optimization of dynamic process in networks
• Diffusion source identification and locating
• Methods to enhance/suppress information diffusion
• Dynamical analysis and control of rumour dissemination
• Dynamical analysis and control of malware spread
• Deep learning and its applications for information diffusion
• New methods and models of massive information data processing and transmitting