Motivated by empirical evidence on the interplay between geography,
population density and societal interaction, we propose a generative process
for the evolution of social structure in cities. Our analytical and simulation
results predict both super-linear scaling of social tie density and information
flow as a function of the population. We demonstrate that our model provides a
robust and accurate fit for the dependency of city characteristics with city
size, ranging from individual-level dyadic interactions (number of
acquaintances, volume of communication) to population-level variables
(contagious disease rates, patenting activity, economic productivity and crime)
without the need to appeal to modularity, specialization, or hierarchy.Comment: Early version of this paper was presented in NetSci 2012 as a
contributed talk in June 2012. An improved version of this paper is published
in Nature Communications in June 2013. It has 14 pages and 5 figure
