Separate Tables: Thematic and Methodological Divisions in Brazilian Political Science<sup>,,</sup>

Sainz, Nilton; Codato, Adriano; Silva, Rodrigo da; Clemente, Augusto

doi:10.1590/1981-3821202400010006

Nilton Sainz

Universidade Federal do Paraná. Departamento de Ciência Política. Curitiba/PR, Brazil

https://orcid.org/0000-0002-3957-2714

Adriano Codato

Universidade Federal do Paraná. Departamento de Ciência Política. Curitiba/PR, Brazil

https://orcid.org/0000-0002-5015-4273

Rodrigo da Silva

Universidade Federal do Paraná. Departamento de Ciência Política. Curitiba/PR, Brazil

https://orcid.org/0000-0001-7051-9391

Augusto Clemente

Universidade Federal do Paraná. Campus Litoral. Matinhos/PR, Brazil

https://orcid.org/0000-0002-9934-1694

Correspondence: Nilton Sainz. E-mail: sainznilton@gmail.com.

Translated by Paulo Scarpa

Figures (11)
Tables (14)

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Figure 01
Network of themes and approaches in Brazilian political science theses and dissertations (2013-2020)

Note: The graph was created using Gephi’s Circle Pack Layout algorithm, organized hierarchically based on modularity class (thematic domains) and weighted degree (the influence of a given term within a specific cluster).

Note: How to interpret the network:Different colors represent different groups (‘clusters’). Clusters indicate the existence of a community of themes, research problems, or concepts that are more intensely shared among themselves than with other terms in the network.

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Figure 02
Network of methodological terms in Brazilian Political Science theses and dissertations (2013-2020)

Note: The graph was created using Gephi’s Circle Pack Layout algorithm, organized hierarchically based on modularity class (thematic domains) and weighted degree (the influence of a given term within a specific cluster).

Note: How to interpret the network:Different colors represent different groups (‘clusters’). Clusters indicate the existence of a community of themes, research problems, or concepts that are more intensely shared among themselves than with other terms in the network.

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Figure 03
Graph of the blue cluster (‘State, government, and international relations’) in the thematic network of Political Science theses and dissertations

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Figure 04
Graph of the Pink Cluster (‘Parties and Elections’) in the Thematic Network of Political Science theses and dissertations

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Figure 05
Graph of the orange cluster (‘Political Theory’) in the thematic network of Political Science theses and dissertations

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Figure 06
Graph of the green cluster (‘Social actors, participation and public policies’) in the thematic network of Political Science theses and dissertations

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Figure 07
Graph of the red cluster (‘Institutions’) in the thematic network of Political Science theses and dissertations

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Figure 08
Graph of the orange cluster in the methodological network of Political Science theses and dissertations

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Figure 09
Graph of the pink cluster in the methodological network of Political Science theses and dissertations

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Figure 10
Graph of the yellow cluster in the methodological network of Political Science theses and dissertations

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Figura 11
Graph of the blue cluster in the methodological network of Political Science theses and dissertation

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Table 01
T&D in Political Science analyzed by higher education institution (2013-2020)

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Table 02
Detail of the lemmatization process in ‘Textometrica’

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Table 03
Central nodes of the thematic network and approaches of theses and dissertations in Political Science from eleven selected Postgraduate Programs (2013-2020)

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Table 04
Summary of the Brazilian Political Science thematic network (2013-2020) by cluster

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Table 05
Metrics of the network of methodological terms in Brazilian Political Science (2013-2020)

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Table 06
ARS metrics of the 10 main nodes in the blue cluster (‘state, government and international relations’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations

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Table 07
ARS metrics of the 10 main nodes in the pink cluster (‘parties and elections’) and edge weights between terms in this subnetwork of the thematic network of political science theses and dissertations

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Table 08
ARS metrics of the 10 main nodes in the orange cluster (‘Political Theory’) and edge weights between terms in this subnetwork of the thematic network of political science theses and dissertations

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Table 09
ARS metrics of the 10 main nodes in the green cluster (‘Social actors, participation and public policies’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations

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Table 10
ARS metrics of the 10 main nodes in the red cluster (‘Institutions’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations

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Table 11
ARS metrics of the 10 main nodes in the orange cluster and edge weights between terms of this subnetwork in the methodological network of Political Science theses and dissertations

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Table 12
ARS metrics of the 10 main nodes in the pink cluster and edge weights between terms of this subnetwork in the methodological network of Political Science theses and dissertations

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Table 13
ARS metrics of the 10 main nodes in the yellow cluster and edge weights between terms of this subnetwork in the methodological network of Political Science theses and dissertations

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Table 14
ARS metrics of the 10 main nodes in the blue cluster and edge weights between terms of this subnetwork in the methodological network of Political Science theses and dissertations

University	Nº of theses	Nº of dissertations	Total	% of the total 1.849
UFRGS	145	111	256	13.85%
USP	81	131	212	11.47%
UFMG	85	121	206	11.14%
UERJ/IESP	124	74	198	10.71%
UFPE	74	114	188	10.17%
UNICAMP	82	76	158	8.55%
UnB	52	106	158	8.55%
UFPR	28	117	145	7.84%
UFSCAR	52	86	138	7.46%
UFF	53	65	118	6.38%
UFPEL	2	70	72	3.89%
Total	778	1.071	1.849	100.0%

Steps	Network 01 (thematic)		Network 02 (methodologic)
Tokenization	total words	21.976	total words	21.976
Selection	selected	1.281	selected	686
Conceptualization	concepts created	451	concepts created	182
Connection	final	758	final	267

Node	Degree centrality (global influence)	Node	Betweenness centrality (main ‘brokers’)	Node	Closeness centrality (shortest path)
state	653	state	0.0359	state	0.8765
theory	629	theory	0.0331	theory	0.8529
institutions	627	public policies	0.0278	institutions	0.8510
public policies	624	institutions	0.0260	public policies	0.8482
case	609	case	0.0250	case	0.8342
national	601	democracy	0.0238	national	0.8269
data	581	national	0.0226	data	0.8093
government	580	government	0.0203	government	0.8085
hypothesis	574	data	0.0180	hypothesis	0.8033
democracy	567	politicians	0.0174	democracy	0.7974

Cluster color	Predominant theme	% nodes (N)	% edges (N)	Central terms within the cluster*
Blue	State, government and international relations	25.6% (195)	7.8% (3.914)	state, national, government, economic, strategies
Pink	Parties and elections	24.3% (185)	10% (4.998)	politicians, parties, elections, legislative, president
Orange	Political theory	23.5% (179)	6.7% (3.366)	theory, democracy, historical, society, rights
Green	Social actors, participation and public policies	19.3% (147)	6% (3.027)	public, actors, participation, agenda, municipalities
Red	Institutions	7.2% (55)	0.9% (480)	institutions, power, federal, decision, trajectory

Source: Elaborated by the authors.

Note: *For a comprehensive list of the top 10 terms within each cluster, see ^{Appendix A} Appendix A Tables 06 to 10. Metrics of the 10 (ten) main nodes in each cluster of the thematic network (Figure 01). Figures 03 to 07. Graphs of each cluster comprising the thematic network (Figure 01). Note: In Tables 06 to 14 (Appendix A and B), we present two important ARS measures: the 10 (ten) nodes with the highest ‘weighted degree’ and the 10 (ten) main nodes based on ‘edge weights’ per cluster (and not the entire network). The ‘weighted degree’ metric allows us to assess the intensity of the nodes (terms, concepts) that serve as focal points within each cluster, taking into account the weight of the connections (edges) that form a given cluster. It is a measure of ‘influence’, albeit ‘localized’. In turn, the ‘edge weights’ demonstrate which connections between nodes have a structural function in the cluster through the frequency of connections between them. It expresses the ‘strength of semantic relationships’ between two particular terms within that cluster. Table 06 ARS metrics of the 10 main nodes in the blue cluster (‘state, government and international relations’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations Rank Node Weighted degree (regional influence) Origin node Destination node Edge weight (strength of the semantic relationship) 01 state 53132 america latina 728 02 government 41728 state government 648 03 national 39500 government lula 624 04 economic 28868 state national 552 05 international 28124 development state 544 06 development 26868 externa international 540 07 strategies 26672 development economic 528 08 organization 24656 state international 524 09 country 22704 government national 492 10 region 20356 economic state 488 Source: Elaborated by the authors. Figure 03 Graph of the blue cluster (‘State, government, and international relations’) in the thematic network of Political Science theses and dissertations Source: Elaborated by the authors. Table 07 ARS metrics of the 10 main nodes in the pink cluster (‘parties and elections’) and edge weights between terms in this subnetwork of the thematic network of political science theses and dissertations Rank Node Weighted degree (regional influence) Origin node Destination node Edge weight (strength of the semantic relationship) 01 parties 37500 parties politicians 1040 02 politicians 36244 elections parties 1036 03 hypothesis 34940 chamber deputies 556 04 elections 34280 elections politicians 548 05 dados 32144 elections vote 504 06 results 28976 dados results 480 07 model 27772 elections president 468 08 literature 26480 deputies legislative 460 09 legislative 23924 campaign elections 448 10 president 19796 candidates elections 444 Source: Elaborated by the authors. Figure 04 Graph of the Pink Cluster (‘Parties and Elections’) in the Thematic Network of Political Science theses and dissertations Source: Elaborated by the authors. Table 08 ARS metrics of the 10 main nodes in the orange cluster (‘Political Theory’) and edge weights between terms in this subnetwork of the thematic network of political science theses and dissertations Rank Node Weighted degree (regional influence) Origin node Destination node Edge weight (strength of the semantic relationship) 01 theory 44760 concept theory 584 02 democracy 36676 democracy theory 576 03 historical 28340 historical theory 444 04 comprehended 25192 concept historical 328 05 concept 22984 comprehended theory 328 06 society 21272 society theory 324 07 rights 19584 gender women 324 08 campo 17052 democracy society 300 09 movement 16640 concept democracy 292 10 discourse 13984 campo theory 284 Source: Elaborated by the authors. Figure 05 Graph of the orange cluster (‘Political Theory’) in the thematic network of Political Science theses and dissertations Source: Elaborated by the authors. Table 09 ARS metrics of the 10 main nodes in the green cluster (‘Social actors, participation and public policies’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations Rank Node Weighted degree (regional influence) Origin node Destination node Edge weight (strength of the semantic relationship) 01 public 55332 case public 628.0 02 case 37944 participation public 500.0 03 methodology 29008 actors public 476.0 04 actors 26188 municipalities public 412.0 05 participation 26060 implementation public 408.0 06 qualitative 19748 methodology public 388.0 07 agenda 19596 agenda public 388.0 08 municipalities 18640 governance public 380.0 09 documents 15356 methodology qualitative 356.0 10 governance 13940 case methodology 348.0 Source: Elaborated by the authors. Figure 06 Graph of the green cluster (‘Social actors, participation and public policies’) in the thematic network of Political Science theses and dissertations Source: Elaborated by the authors. Table 10 ARS metrics of the 10 main nodes in the red cluster (‘Institutions’) and edge weights between terms in this subnetwork of the thematic network of Political Science theses and dissertations Rank Node Weighted degree (regional influence) Origin vertex Destination node Edge weight (strength of the semantic relationship) 1 institutions 53568 institutions power 580 2 power 35924 federal institutions 480 3 federal 27560 decision institutions 392 4 decision 22364 constitution institutions 360 5 constitution 15652 decision power 340 6 lei 14512 federal tribunal 328 7 trajectory 14360 stf tribunal 320 8 tribunal 9896 federal power 312 9 justice 9440 judiciary power 308 10 ministry 9232 federal stf 292 Source: Elaborated by the authors. Figure 07 Graph of the red cluster (‘Institutions’) in the thematic network of Political Science theses and dissertations Source: Elaborated by the authors. .

Cluster color	Predominant theme	% Node (n)	% Edges (n)	Predominant methodological terms	Frequent verbs
Orange	Political Theory	31.8% (85)	11.4% (2,937)	historical, problem, concept	comprehend, discuss
Pink	Parties & Elections	30.7% (82)	10.6% (2,733)	hypotheses, data, model	explain, compare
Yellow	“Political communication”	22.1% (59)	4.6% (1,187)	qualitative, content, quantitative	interview, collect
Blue	State, Gov. & IR; Actors & PP; Institutions	15.3% (41)	2.6% (677)	case, conditions, economic	analyze, identify

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	state	53132	america	latina	728
02	government	41728	state	government	648
03	national	39500	government	lula	624
04	economic	28868	state	national	552
05	international	28124	development	state	544
06	development	26868	externa	international	540
07	strategies	26672	development	economic	528
08	organization	24656	state	international	524
09	country	22704	government	national	492
10	region	20356	economic	state	488

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	parties	37500	parties	politicians	1040
02	politicians	36244	elections	parties	1036
03	hypothesis	34940	chamber	deputies	556
04	elections	34280	elections	politicians	548
05	dados	32144	elections	vote	504
06	results	28976	dados	results	480
07	model	27772	elections	president	468
08	literature	26480	deputies	legislative	460
09	legislative	23924	campaign	elections	448
10	president	19796	candidates	elections	444

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	theory	44760	concept	theory	584
02	democracy	36676	democracy	theory	576
03	historical	28340	historical	theory	444
04	comprehended	25192	concept	historical	328
05	concept	22984	comprehended	theory	328
06	society	21272	society	theory	324
07	rights	19584	gender	women	324
08	campo	17052	democracy	society	300
09	movement	16640	concept	democracy	292
10	discourse	13984	campo	theory	284

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	public	55332	case	public	628.0
02	case	37944	participation	public	500.0
03	methodology	29008	actors	public	476.0
04	actors	26188	municipalities	public	412.0
05	participation	26060	implementation	public	408.0
06	qualitative	19748	methodology	public	388.0
07	agenda	19596	agenda	public	388.0
08	municipalities	18640	governance	public	380.0
09	documents	15356	methodology	qualitative	356.0
10	governance	13940	case	methodology	348.0

Rank	Node	Weighted degree (regional influence)	Origin vertex	Destination node	Edge weight (strength of the semantic relationship)
1	institutions	53568	institutions	power	580
2	power	35924	federal	institutions	480
3	federal	27560	decision	institutions	392
4	decision	22364	constitution	institutions	360
5	constitution	15652	decision	power	340
6	lei	14512	federal	tribunal	328
7	trajectory	14360	stf	tribunal	320
8	tribunal	9896	federal	power	312
9	justice	9440	judiciary	power	308
10	ministry	9232	federal	stf	292

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	comprehended	6338	comprehended	historical	103
02	historical	4683	comprehended	concept	90
03	importance	4316	comprehended	understand	84
04	concept	4203	concept	historical	82
05	discussion	3918	comprehended	importance	80
06	understand	3896	central	comprehended	66
07	investigate	3855	comprehended	investigate	66
08	meaning	3412	comprehended	meaning	65
09	approach	3316	historical	understand	60
10	central	3272	concept	discussion	60

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	hypothesis	6011	results	dados	120
02	dados	5875	dados	hypothesis	98
03	results	5421	literature	dados	88
04	model	5068	results	hypothesis	87
05	literature	4815	literature	hypothesis	83
06	comparative	3463	hypothesis	model	81
07	variable	3421	hypothesis	test	79
08	factors	3324	results	model	77
09	explain	3171	literature	results	76
10	level	2991	results	variable	75

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	methodology	5555	methodology	qualitative	83.0
02	qualitative	3422	documents	methodology	58.0
03	documents	2764	interviews	documents	54.0
04	interviews	2226	documents	qualitative	47.0
05	information	2205	methodology	quantitative	42.0
06	content	2095	interviews	qualitative	39.0
07	techniques	1798	content	methodology	38.0
08	adopted	1660	bibliographical	documents	37.0
09	bibliographical	1655	methodology	techniques	36.0
10	redes	1617	revision	bibliographical	35.0

Rank	Node	Weighted degree (regional influence)	Origin node	Destination node	Edge weight (strength of the semantic relationship)
01	analyze	8665	analyze	case	129
02	case	6214	analyze	identify	104
03	identify	4820	analyze	influence	80
04	influence	3979	analyze	characteristics	77
05	characteristics	3576	case	identify	75
06	interesses	3397	groups	interesses	72
07	observe	3198	analyze	groups	71
08	groups	3009	analyze	observe	71
09	conditions	2744	analyze	conditions	66
10	relevance	2605	analyze	interesses	66

[1] Correspondence: Nilton Sainz. E-mail: sainznilton@gmail.com.

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