ﻻ يوجد ملخص باللغة العربية
Though many aggregation theories exist for physical, chemical and biological systems, they do not account for the significant heterogeneity found, for example, in populations of living objects. This is unfortunate since understanding how heterogeneous individuals come together in support of an extremist cause, for example, represents an urgent societal problem. Here we develop such a theory and show that the intrinsic population heterogeneity can significantly delay the gel transition point and change the gels growth rate. We apply our theory to examine how humans aggregate online in support of a particular extremist cause. We show that the theory provides an accurate description of the online extremist support for ISIS (so-called Islamic State) which started in late 2014.
We construct a model of social behaviour through the dynamics of interacting agents. The agents undergo game-theoretic interactions where each agent can decide to lend support to particular other agents or otherwise, and agents are rewarded according
We show that the eclectic Boogaloo extremist movement that is now rising to prominence in the U.S., has a hidden online mathematical order that is identical to ISIS during its early development, despite their stark ideological, geographical and cultu
The correlation length $xi$, a key quantity in glassy dynamics, can now be precisely measured for spin glasses both in experiments and in simulations. However, known analysis methods lead to discrepancies either for large external fields or close to
An imperative condition for the functioning of a power-grid network is that its power generators remain synchronized. Disturbances can prompt desynchronization, which is a process that has been involved in large power outages. Here we derive a condit
While frameworks based on physical grounds (like the Drift-Diffusion Model) have been exhaustively used in psychology and neuroscience to describe perceptual decision-making in humans, analogous approaches for more complex situations like sequential