SpringerBriefs in Computer Science Computational Infodemiology

font-family: 'Calibri',sans-serif;">To map the impact of uncertainty, certain indicators need to be tracked, and within the scale-free network, social stress indicators are introduced. By incorporating social stress indicators, belief system mapping becomes viable and possible to model misinformation spread within an echo chamber. Computational Infodemiology is a novel discipline that maps the indicators that underpin digital discourse. Being able to fundamentally map belief systems within a scale free network and provide a framework by which the evolution of belief can be mapped, outlines the impact uncertainty has on an echo chamber and models the spread of misinformation. This book provides the framework and empirical data to outline these scenarios. To map the impact of uncertainty, certain indicators need to be tracked, and within the scale-free network, social stress indicators are introduced. These social stress indicators serve as a proxy for potential harm and can differentiate between low, medium and high levels of harm. By incorporating social stress indicators, belief system mapping becomes viable and possible to model misinformation spread within an echo chamber.