  Elections, specially in countries such as Brazil with an electorate of the
order of 100 million people, yield large-scale data-sets embodying valuable
information on the dynamics through which individuals influence each other and
make choices. In this work we perform an extensive analysis of data sets
available for Brazilian proportional elections of legislators and city
councillors throughout the period 1970-2012, which embraces two distinct
political regimes: a military dictatorship and a democratic phase. Through the
distribution $P(v)$ of the number of candidates receiving $v$ votes, we perform
a comparative analysis of different elections in the same calendar and as a
function of time. The distributions $P(v)$ present a scale-free regime with a
power-law exponent $\alpha$ which is not universal and appears to be
characteristic of the electorate. Moreover, we observe that $\alpha$ typically
increases with time. We propose a multi-species model consisting in a system of
nonlinear differential equations with stochastic parameters that allows to
understand the empirical observations. We conclude that the power-law exponent
$\alpha$ constitutes a measure of the degree of feedback of the electorate
interactions. To know the interactivity of the population is relevant beyond
the context of elections, since a similar feedback may occur in other social
contagion processes.
