In-Silico Sandbox to Model Multi-Platform Computational Disinformation

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This proposed research program aims to advance quantitative methods in modeling social networks and opinion dynamics, addressing a research gap about the growing concern around disinformation campaigns via social media platforms. Research on opinion dynamics, particularly the propagation of "false news" across multiple social media platforms, is growing but often outpaced by developments on social media platforms. Recent advances in extant literature focus on detecting and characterizing false news that propagates on social media, leaving challenges and open questions, including the efficacy of algorithmic interventions in preventing the spread of disinformation. This research program seeks to create a statistically representative synthetic environment of the Canadian social media environment using agent-based modeling techniques to simulate multi-platform network mechanisms, social interactions, and opinion dynamics. The focus is on developing new methods necessary to create and inform this realistic simulator that captures underlying complexity and heterogeneity but remains tractable for computational experimentation. The short-term objectives of the program are: 1) Model and construct a synthetic population of the social media environment that statistically represents user characteristics, opinions and interaction behavior, and network patterns; 2) Develop computational algorithms to capture and impute distributions of the agent, network, and opinion characteristics from empirical data; 3) Build a computational agent-based model simulator that statistically recreates the dynamics of social media networks and opinions endogenously; and 4) Create an in silico sandbox to test the effects of algorithmic intervention mechanisms. The outcome of the proposed program will be a realistic computational simulator of the Canadian social media environment that captures the complexity of human and social behavior, opinion dynamics, and complex network dynamics across multiple social media platforms. This proposal will lead to new methods that inform applications in an area of immediate importance - opinion dynamics via social media discourse. The methods we develop will have the potential to lead to novel discoveries in social dynamics. If successful, the proposed computational simulator will also help inform social media organizations and public institutions on developing interventions to guard against the specter of disinformation.