Sociophysics and Econophysics explore rules and regularizes the social and economic system, and therefore become the foundations of current computational social sciences. Inspired by the basis in physics, major attempts have recently been made in extracting the statistical properties, network structures, and collective dynamics of various social systems. These include developing models of financial or market systems, correlations of various stock or commodity prices, their dynamics as well as their mapped structures, kinetic exchange models of market dynamics and of spontaneous opinion formations in societies, and analysis of election results in these contexts, spin-glass or neural network-like modeling of social (collective and iterative) learning in sharing scarce resources in Minority Games, etc. These are some examples of extensively studied socio-dynamical model systems, with encouraging results.
Physics, economics, finance, sociology, mathematics, engineering, and computer science are fields of science that, as a result of cross-fertilization, have created the multi-, cross-, and interdisciplinary areas of science and research such as Sociophysics and Econophysics, thriving in recent years. It is encouraged that researchers use knowledge, methodologies, methods, and tools of physics for modeling, explaining, and forecasting economic and social phenomena and processes. Meaningful Sociophysics and Econophysics necessitate both data and model or theory. Interdisciplinary approaches are appreciated more than traditional physics, sociology, and economics. New analytical tools and new data can be developed by researchers and convincing results are welcomed. The special issue aims to the wide landscape of research of bridging the gap between methods and discoveries from physics to social and economic system.
Scope and Information for authors: the main scientific targets include (but not limited to)
• To develop, analyze and implement interdisciplinary and complex systems, e.g., complex networks, human mobility, epidemic models, machine learning and statistical learning, artificial intelligence, deep learning, etc.
• To develop, analyze and implement numerical methods for dealing with highly sophisticated mathematical models in finance and economy, e.g., resilience models, evolution mechanisms, dynamics of information, high-dimensional systems, etc.
• To apply network modeling to study systemic risk in social-economic systems from macro-complexity or the interconnectedness of all things to microscopic failure and recovery models, finding key mechanisms and means to improve the stability of such systems under perturbation and its robustness against failures.
• To study the emergence of social-economic behavior and opinions in local populations by using data-driven models of social networks, social influence, opinion dynamics, information processing, textual analysis, the spread of influence or innovations diffusion, etc.
Sociophysics and Econophysics explore rules and regularizes the social and economic system, and therefore become the foundations of current computational social sciences. Inspired by the basis in physics, major attempts have recently been made in extracting the statistical properties, network structures, and collective dynamics of various social systems. These include developing models of financial or market systems, correlations of various stock or commodity prices, their dynamics as well as their mapped structures, kinetic exchange models of market dynamics and of spontaneous opinion formations in societies, and analysis of election results in these contexts, spin-glass or neural network-like modeling of social (collective and iterative) learning in sharing scarce resources in Minority Games, etc. These are some examples of extensively studied socio-dynamical model systems, with encouraging results.
Physics, economics, finance, sociology, mathematics, engineering, and computer science are fields of science that, as a result of cross-fertilization, have created the multi-, cross-, and interdisciplinary areas of science and research such as Sociophysics and Econophysics, thriving in recent years. It is encouraged that researchers use knowledge, methodologies, methods, and tools of physics for modeling, explaining, and forecasting economic and social phenomena and processes. Meaningful Sociophysics and Econophysics necessitate both data and model or theory. Interdisciplinary approaches are appreciated more than traditional physics, sociology, and economics. New analytical tools and new data can be developed by researchers and convincing results are welcomed. The special issue aims to the wide landscape of research of bridging the gap between methods and discoveries from physics to social and economic system.
Scope and Information for authors: the main scientific targets include (but not limited to)
• To develop, analyze and implement interdisciplinary and complex systems, e.g., complex networks, human mobility, epidemic models, machine learning and statistical learning, artificial intelligence, deep learning, etc.
• To develop, analyze and implement numerical methods for dealing with highly sophisticated mathematical models in finance and economy, e.g., resilience models, evolution mechanisms, dynamics of information, high-dimensional systems, etc.
• To apply network modeling to study systemic risk in social-economic systems from macro-complexity or the interconnectedness of all things to microscopic failure and recovery models, finding key mechanisms and means to improve the stability of such systems under perturbation and its robustness against failures.
• To study the emergence of social-economic behavior and opinions in local populations by using data-driven models of social networks, social influence, opinion dynamics, information processing, textual analysis, the spread of influence or innovations diffusion, etc.
