Fig 1.
Supervised learning for document classification.
Table 1.
Related work.
Fig 2.
The framework for analysis of administrative decrees.
Fig 3.
Process of creation of taxonomies.
Fig 4.
LDAvis results for abstract only.
Table 2.
Top 5 LDAvis terms for abstract analysis using λ = 0.4.
Fig 5.
LDAvis results for full decree.
Table 3.
Top 5 LDAvis terms for full decree using λ = 0.4.
Table 4.
Cabinets-based taxonomy description.
Table 5.
Senate-based taxonomy description.
Fig 6.
Co-sponsorship of cabinets’ policy-areas.
The main diagonal stands for the number of decrees with only one label.
Fig 7.
Collaboration between areas from the perspective of the Senate-based taxonomy.
The main diagonal stands for the number of decrees with only one label.
Fig 8.
Overlap between the Senate and cabinets-based taxonomies.
Fig 9.
Number of decrees per year from the perspective of the Senate-based taxonomy focusing on the top 4 areas most issued in 2019.
Fig 10.
Number of decrees per year from the perspective of the cabinets-based taxonomy focusing on the top 4 areas most issued in 2019.
Table 6.
F1-score for the Senate-based taxonomy models.
Table 7.
F1-score for the cabinets-based taxonomy models.
Table 8.
Characteristics of the administrative decrees network.
Fig 11.
Disconnected decrees per year.
Proportion of disconnected decrees given by (number of disconnected decrees)÷(total number of decrees in a year).
Table 9.
Taxonomies’ 100 most central nodes.
Table 10.
Top 5 decrees according to degree centrality.
Table 11.
Top 5 decrees according to betweenness centrality.
Table 12.
PAC cluster: Senate and cabinets taxonomies.
Areas that are not present in this cluster were omitted.