Nonlinear scaling in social Physics

Abstract

The applications of statistical mechanics in the study of collective human behavior is not a novelty. However, in the past few decades we shaw a huge spike of interest on the study of society using physics. In this thesis we explore nonlinear scaling laws in social systems using physical techniques. First we perform data analysis and modeling applied to elections. We show that the number of votes of a candidate scales nonlinear with the money spent at the campaign. To our surprise, the correlation revealed a sublinear scaling, which means that the average “price” of one vote grows as you increase the number of votes. Using a mean-field model we find that the sublinearity emerges from the competition and the distribution of votes is causally determined by the distribution of money campaign. Moreover, we show that the model is able to reasonably predict the final number of valid votes through a simple heuristic argument. Lastly, we present our work on allometric scaling of social indicators. We show how homicides, deaths in car crashes, and suicides scales with the population of Brazilian cities. Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, which reveal a possible evidence for social influence on suicides occurrences.