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Using Government Data to Uncover Political Power and Influence of Contemporary Slavery Agents in Brazil

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Big Social Data and Urban Computing (BiDU 2018)

Abstract

This work uses open data published by the Brazilian government to investigate connections between agents involved on contemporary slavery labor and politicians, evaluating their power and influence. A network was built on data from Brazilian elections and campaign donations since 2002, including all candidates and donors associated to slave labor. Not only 263 direct candidatures from slavery agents were identified, but also more than 40 million Brazilian Reais in campaign donations for candidates for all electoral positions, showing a strong relation between slavery agents and Brazilian politicians. Data were also analyzed using metrics based on sociologist Manuel Castells’ Network Theory of Power that measure how much power and influence each donation is accounted for, in addition to its absolute amount. The resulting network was semantically enriched and modeled according to existing ontologies and published in RDF using Linked Open Data standards in a semantic knowledge graph, allowing information to be identified, disambiguated and interconnected by software agents in future research.

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Notes

  1. 1.

    CPF is the fiscal identification of Brazilian citizens. CNPJ is the fiscal identification of Brazilian companies.

  2. 2.

    Partnership between ILO and Brazilian Labor Department of Justice.

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Acknowledgments

The authors would like to thank CNPq and FAPERJ for partially supporting this work.

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Correspondence to Letícia Dias Verona .

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Verona, L.D., Lopes, G.R., Campos, M.L.M. (2019). Using Government Data to Uncover Political Power and Influence of Contemporary Slavery Agents in Brazil. In: Oliveira, J., Farias, C., Pacitti, E., Fortino, G. (eds) Big Social Data and Urban Computing. BiDU 2018. Communications in Computer and Information Science, vol 926. Springer, Cham. https://doi.org/10.1007/978-3-030-11238-7_8

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  • DOI: https://doi.org/10.1007/978-3-030-11238-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11237-0

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