Social network analysis against corruption: a study of the public budget related to the Covid-19 pandemic
DOI:
https://doi.org/10.11606/issn.1982-6486.rco.2022.191515Keywords:
Social network analysis, Graph, Corruption, PandemicAbstract
The fight against the Covid-19 pandemic triggered almost immediate reactions from governments worldwide. Economic resources were requested to maintain the economy and help families and businesses, causing unprecedented changes in public budgets. However, this context opened a window of opportunity for corruption, an evil that afflicts all societies. Against this backdrop, this study captured budget data and applied social network analysis and graph mining techniques to examine the 2020 Brazilian extraordinary federal budget related to Covid-19, searching for signs of corruption in municipalities. The results indicate the potential of the graph approach to identify municipalities more susceptible to corruption since studying the relationships between companies and municipalities offers investigative insights that would probably not be achieved through traditional models. The findings are a valuable source for scholars and practitioners looking for methods to improve the work of monitoring and control agencies and law enforcement.
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