Fig. 7

Different dynamic parameters generate distinct forms of degree distributions. Left Panel: For a fixed value of confined space, p_s=0.035, two distributions are shown, one with higher p_f (red triangles) juxtaposed to a fitted log normal (black dotted line), and the other with a smaller p_f (purple circles) fitted to a power law. Lower p_f, means nodes spend more time inside \(\mathcal {P}\), which allows for more in-confinement connections, then increasing degree heterogeneity. Both curves emerge from initial random networks with N=10⁴ and 〈k〉=4. Right panel: Comparison with a real network obtained from the Brazilian Federal Police (see text for details of the data) (da Cunha and Gonçalves 2018). As the real data has M=0.96 and C=0.43, the degree distribution obtained from the model corresponds to the parameters that give the largest M and C. Even when they are not as large as the real ones, the similarity between both distributions is remarkable