Plot the number of people killed in terrorists attacks around the world since 1968 against the frequency with which such attacks occur and you’ll get a power law distribution, that’s a fancy way of saying a straight line when both axis have logarithmic scales.
The question, of course, is why? Why not a normal distribution, in which there would be many orders of magnitude fewer extreme events?
Aaron Clauset and Frederik Wiegel have built a model that might explain why. The model makes five simple assumptions about the way terrorist groups grow and fall apart and how often they carry out major attacks. And here’s the strange thing: this model almost exactly reproduces the distribution of terrorists attacks we see in the real world.
These assumptions are things like: terrorist groups grow by accretion (absorbing other groups) and fall apart by disintegrating into individuals. They must also be able to recruit from a more or less unlimited supply of willing terrorists within the population.
Being able to reproduce the observed distribution of attacks with such a simple set of rules is an impressive feat. But it also suggests some strategies that might prevent such attacks or drastically reduce them in number . One obvious strategy is to reduce the number of recruits within a population, perhaps by reducing real and perceived inequalities across societies.
Easier said than done, of course. But analyses like these should help to put the thinking behind such ideas on a logical footing.
Ref: arxiv.org/abs/0902.0724: A Generalized Fission-Fusion Model for the Frequency of Severe Terrorist Attacks