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In Brazil, individual curricula vitae of academic researchers, that are mainly composed of professional information and scientific productions, are managed into a single software platform called Lattes. Currently, the information gathered from this platform is typically used to evaluate, analyze and document the scientific productions of Brazilian research groups. Despite the fact that the Lattes curricula has semi-structured information, the analysis procedure for medium and large groups becomes a time consuming and highly error-prone task. In this paper, we describe an extension of the script Lattés (an open-source knowledge extraction system from the Lattes platform), for analysing individuals Lattes curricula and automatically discover large-scale co-authorship networks for any academic area. Given some knowledge domain (academic area), the system automatically allows to identify researchers associated with the academic area, extract every list of scientific productions of the researchers, discretized by type and publication year, and for each paper, identify the co-authors registered in the Lattes Platform. The system also allows the generation of different types of networks which may be used to study the characteristics of academic areas at large scale. In particular, we explored the node's degree and Author Rank measures for each identified researcher. Finally, we confirm through experiments that the system facilitates a simple way to generate different co-authorship networks. To the best of our knowledge, this is the first study to examine large-scale co-authorship networks for any Brazilian academic area.