Strong Social Networks

A well-written article (pdf) reports on the work by Oxford folks (previous post). Plus, it says that a "pair of Oxford physicists, Neil Johnson and Sean Gourley, have teamed up with social scientists at the Conflict Analysis Resource Center (CERAC), based in Bogotá"

"When the researchers graphed all the attacks within a given conflict, with the number of attacks plotted against the number killed in each, it produces a fat-tailed exponential curve. And the exponent of the function, which determines the curve’s shape, is nearly always the same. “Terrorism and guerrilla warfare everywhere in the world has a signature of about 2.5,” says Gourley. Plotting the distribution of these events over time produces another, distinctive signature.

Robustness of community structure in networks

"The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated." Source