Sunday, January 31, 2021

An avalanche of violence: New analysis reveals predictable patterns in armed conflicts

Recommendable! Towards a more peaceful world!

"... present a new model using data from armed conflict in Africa that explains how conflicts spread over a geographic region. More technically, the model describes the scale-free ways that clusters of violent interactions grow and spread over time and space. ...
“Your intuition says each of these conflicts should be a consequence of specific social and cultural dynamics,” ... “but then you do the analyses and you find that in fact these seemingly different conflicts are characterized by the same patterns.” ...
discovered the general patterns by looking at how an initial event spreads and ignites conflicts in other regions. ... likens these “conflict avalanches” to well-known cascades in nature. If you add enough sand to a pile, for example, the sides will eventually become so steep that a single new grain can create an avalanche. By virtue of collapse, however, the slope flattens and allows another build-up. ...
These cascade dynamics might seem to explain large variation among conflict outbreaks, with some petering out quickly and others generating long-lasting conflagrations. ... in their work, have also found it essential to account for regional variation. Not only is conflict much more frequent and intense in some regions compared to others, the spatial variation in intensity may itself follow a scaling law. ..."

"Armed conflict data display features consistent with scaling and universal dynamics in both social and physical properties like fatalities and geographic extent. We propose a randomly branching armed conflict model to relate the multiple properties to one another. ...
We show how this approach akin to thermodynamics imparts mechanistic intuition and unifies multiple conflict properties, giving insight into causation, prediction, and intervention timing."

An avalanche of violence: New analysis reveals predictable patterns in armed conflicts | Santa Fe Institute

Here is the link to the referenced paper:

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