This is the abstract and slides of my talk about Analysis of Mexico’s drug-cartels network at the Conference of Complex Systems’ satellite Computational Social Sciences.
Violence linked to drug traffic in Mexico has increased the last ten years, the reasons of this spread are difficult to quantify. However, a relevant feature to take into account is the large number of drug cartels and the disruption of them into small violent cells.
Many strategies have been proposed to dismantle the operation networks of these criminal groups, being the capture attempt of the cartel leaders the most usual one. This strategy has not have a significant positive outcome decreasing the influence of these groups neither the violence around the country. In this sense, the complex network theory approach emerges as an alternative to understand the dynamics underlying this no-trivial phenomenon. In this approach, a network is composed by nodes such as people, places, cities, etc., and links represent any kind of relashionship between said nodes.
In this work, by means of a semi-automated text mining tool we construct a network of the characters of the Anabel Hernandez’s book “Los señores del narco” in order to analyze it’s topological and dynamical properties. By performig directed attacks to the most relevant nodes of the network using different centralities, we measure the robustness of this network in terms of the size of the giant component i.e. optimal percolation. We also analyze the resulting network communities after these attacks and observe the exact amount of removed characters needed to dismantle this giant component.
With this approach it is possible not only to propose a minimal quantity of characters to be removed from the network to desmantle it but also if there are differences between the most socially influential nodes and those who are important to the network topology. These kind of approaches could aquire relevance in terms of developing strategies to disable complex criminal structures.