The quality of public information is now subject to 24-7 news cycles on multiple media platforms alongside user-generated commentary. Information security is critical when it comes to the cyber global information environment where the internet and social media, as the primary sources of information and news, are actively used to influence opinion and activities, disseminate false information, and manipulate the perception of the world. Therefore, it is crucial to study the information exchange dynamics to understand the reach of any information available in the online environment and to compare putatively different methodologies and theoretical perspectives (from generative socio-cognitive agents to deep learning and between). However, modeling information exchange dynamics is a challenging problem due to complex non-trivial individual and emergent collective human behaviors in receiving, processing, and transmitting information; and it requires the development of next-generation of agent-based modeling approaches that incorporate theory and methods from multiple disciplines including network and computational social science, social psychology, cognitive science, sociology, economics, big data science, artificial intelligence, and machine learning, communication science and information theory.

We are seeking submissions on the following topics:

Agent-based simulations of social media platforms.
Models of information spread and evolution.
Social network analysis and data mining studies to inform the development of agent-based models.
Explainable models of social phenomena.
Ontologies and taxonomies for describing social media platforms.
Verification and validation methods for social simulations.
Rigorous methods and metrics to quantitatively assess the accuracy and scalability of models.
Digital media studies on narrative within social media platforms.
Constraints on agent behavior from neuroscience, psychology and social science.