A new pretopological way of identifying spreaders in propagation diffusion phenomena

In a world that's increasingly connected, many crises are related to propagation phenomena where we need to either repress the spreading (e.g. epidemics, computer viruses, fake news...) or try to accelerate it (e.g. the diffusion of a new anti-virus patch). A good understanding of such phenomena involves a knowledge of both the structure of the whole system and the specifics of the transmission process. The standard way to deal with the former has been through a characterization of the structure by the use of networks, where nodes are the components of the system where the propagation occurs, and links exist between them if there's a possibility of transmission from one component to the other. This allows to identify the super-spreaders (i.e. components that diffuse in a disproportionally large amount) as nodes with certain particular network properties. Here we propose the use of pretopology as a framework to characterize the structure of a system, as well as a new pretopological metric for the identification of super-spreaders. Since the metric can easily be transformed into an equivalent network metric, it is easy to compare its performance with some of the classical network indices of node importance. The relevance of the metric is tested by the use of some standard agent-based models of epidemics and opinion dynamics. Finally, a pretopological model of opinion diffusion is also proposed and studied

Policy Implications of Economic Complexity and Complexity Economics

Complexity economics has developed into a promising cutting-edge research program for a more realistic economics in the last three or four decades. Also some convergent micro- and macro-foundations across heterodox schools have been attained with it. With some time lag, boosted by the financial crisis 2008ff., a surge to explore economic complexity’s (EC) policy implications emerged. It demonstrated flaws of “neoliberal” policy prescriptions mostly derived from the neoclassical mainstream and its relatively simple and teleological equilibrium models. However, most of the complexity-policy literature still remains rather general. Therefore, policy implications of EC are reinvestigated here. EC usually is specified by “Complex Adaptive (Economic) Systems” [CA(E)S], characterized by mechanisms, dynamic and statistical properties such as capacities of “self-organization” of their components (agents), structural “emergence”, and some statistical distributions in their topologies and movements. For agent-based systems, some underlying “intentionality” of agents, under bounded rationality, includes improving their benefits and reducing the perceived complexity of their decision situations, in an evolutionary process of a population. This includes emergent social institutions. Thus, EC has manifold affinities with long-standing issues of economic heterodoxies, such as uncertainty or path- dependent and idiosyncratic process. We envisage a subset of CA(E)S, with heterogeneous agents interacting, in the “evolution-of-cooperation” tradition. We exemplarily derive some more specific policy orientations, in a “framework” approach, embedded in a modern “meritorics”, that we call Interactive Policy