Mapping Power and Collaboration in Urban Data Governance: A Complex Network Analysis of Social Actors in Brazil
Resumo
Urban data governance is increasingly shaped by sociotechnical infrastructures that may reproduce structural inequalities, particularly in Global South contexts. This paper examines how social actors are structured and interconnected in urban data governance in Brazil through the GHZ Network, combining Social Network Analysis (SNA) and critical data studies. Based on documentary research and relational sampling, we constructed a network of 35 core actors and 809 connected entities, modeling collaborations, funding relations, and data exchanges. Results reveal a sparse yet highly connected network, dependent on a small number of intermediary actors—primarily civil society organizations—while public sector actors exhibit low centrality. The analysis also highlights territorial concentration in Brazil’s South–Southeast and the influence of international funders, pointing to governance asymmetries. The study contributes a replicable framework for mapping sociotechnical networks and provides insights into how network structures relate to power and inequality in urban data governance.Referências
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Batty, M. (2013). The new science of cities. MIT Press.
Bertalanffy, L. von. (2010). Teoria geral dos sistemas: Fundamentos, desenvolvimento e aplicações (F. M. Guimarães, Trad.). Editora Vozes. (1ª ed. 1968).
Brasil. (2018). Estratégia brasileira para a transformação digital – E-Digital: Ciclo 2018–2022. Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC).
Brasil. (2022). Estratégia brasileira para a transformação digital (E-Digital): Ciclo 2022–2026. Centro de Gestão e Estudos Estratégicos (CGEE) & Ministério da Ciência, Tecnologia e Inovações (MCTI).
Broussard, M. (2018). Artificial unintelligence: How computers misunderstand the world. MIT Press.
Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.
D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press.
Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
Kitchin, R., & Dodge, M. (2014). Code/space: Software and everyday life. MIT Press.
Morin, E. (2015). Introdução ao pensamento complexo (E. Lisboa, Trad.). Sulina. (1ª ed. 1990).
Morin, E., & Le Moigne, J.-L. (2000). A inteligência da complexidade (N. Maria, Trad.). Fundação Peirópolis. (1ª ed. 1999).
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.
Obendiek, A. S. (2023). Data governance: Value orders and jurisdictional conflicts. Oxford University Press.
Perez, C. C. (2019). Invisible women: Exposing data bias in a world designed for men. Random House.
Townsend, A. (2015). Cities of data: Examining the new urban science. Public Culture, 27(2), 201–212.
Publicado
19/07/2026
Como Citar
CAVALCANTI, Isabella; TRAMONTANO, Marcelo.
Mapping Power and Collaboration in Urban Data Governance: A Complex Network Analysis of Social Actors in Brazil. In: LATIN AMERICAN SYMPOSIUM ON DIGITAL GOVERNMENT (LASDIGOV), 14. , 2026, Gramado/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 229-240.
ISSN 2763-8723.
DOI: https://doi.org/10.5753/lasdigov.2026.23459.
