Redes de migração no Brasil: estrutura e dinâmica dos fluxos migratórios intermunicipais nos anos 2000 e 2010

Abstract

Internal migration in the 21st century has become more dynamic, driven by economic, political, and social factors. In this context, spatial network analysis constitutes a relevant methodological tool for understanding population movements that are in constant transformation, as it enables the examination of connections between places and people, as well as the relational structure and composition of migratory flows. Furthermore, this analytical perspective allows for the analysis of more disaggregated geographical units, such as municipalities, facilitating the identification of the extent and spatial dispersion of migration networks. The main objective of this dissertation is to analyze the structure and dynamics of spatial migration networks between Brazilian municipalities, incorporating graph theory to identify trends and patterns within Brazil's migratory networks. The research adopted a methodology based on network analysis, grounded in graph theory, using data from the 2000 and 2010 Demographic Censuses and employing the Gephi software for network modeling and visualization. The results revealed greater integration within the Brazilian migratory network in 2010, with an increase in the number of connections, average degree, and link density, accompanied by a reduction in network diameter. This decrease in diameter, together with the increase in edge density, suggests a transition from a more hierarchical topology to a more distributed structure. Large urban centers, such as São Paulo and Brasília, remained strategic hubs, though with reduced centrality, reflecting a decentralization process and the emergence of new regional poles. Regarding the analysis of network profiles, significant differences were identified by gender, age, and education level, reflecting specific dynamics of displacement and connection between municipalities. With greater concentration in urban areas, female migration became predominant in the 2010 network, while a process of aging among the migrant population was observed over time. The composition of the network by education level revealed distinct topologies: migrants with low levels of education showed higher clustering coefficients in major urban centers and state capitals, whereas those with higher education formed more sparse and decentralized networks. These findings highlight the need for public policies that take into account the multifaceted nature of migration dynamics.