Quantifying social segregation in large-scale networks.

We present a measure of social segregation which combines mobile phone data and income register data in Oslo, Norway. In addition to measuring the extent of social segregation, our study shows that social segregation is strong, robust, and that social networks are particularly clustered among the richest. Using location data on the areas where people work, we also examine whether exposure to other social strata weakens measured segregation.

Emergence of scaling in complex substitutive systems.

Diffusion processes are central to human interactions. One common prediction of the current modelling frameworks is that initial spreading dynamics follow exponential growth. Here we find that, for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields, early growth patterns follow a power law with non-integer exponents.

Product diffusion through on-demand information-seeking behaviour.

Most models of product adoption predict S-shaped adoption curves. Here we report results from two country-scale experiments in which we find adoption curves. We show evidence that the observed linear pattern is the result of active information-seeking behaviour: individuals actively pulling information from several central sources facilitated by modern Internet searches.

Mapping poverty using mobile phone and satellite data.

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses.

Correlation length exponent in the three-dimensional fuse network.

We present numerical measurements of the critical correlation length exponent nu in the three-dimensional fuse model. Using sufficiently broad threshold distributions to ensure that the system is the strong-disorder regime, we determine nu to be nu=0.83+/-0.