Prof. Eduardo A. Haddad

Lecture 28: Scientific Networks

2

Introduction

Universities and regional development

Importance of universities in a regional innovation system

Knowledge spillovers

Evidences of spatial localization

Scientific landscape in 1990 -2010

Accelerated growth of production in emerging scientific

nations (China, Brazil and India)

Increase of scientific collaboration (over 70% of their

production from domestic collaboration)

Spatial scientometrics

Analyzes spatial patterns of scientific activity

The importance of geography in process of creation and

diffusion of knowledge

3

Colaboração científica

A ciência moderna é cada vez mais colaborativa

O aumento da colaboração científica revela-se de

muitas maneiras:

Número de participações em projetos de

pesquisa

Número de orientações acadêmicas

Número de coautorias acadêmicas

4

Caso brasileiro

5

Colaboração científica

Embora existam diferenças claras entre áreas nos

números absolutos de artigos de coautoria, todas as

áreas apresentam um padrão semelhante

6

Artigos em coautoria estão se tornando mais frequentes

Brasil (1990-2010): Área de Ciências Exatas

7

Na área de Matemática (no mundo)...

8

Scientific collaboration in numbers

How to measure scientific collaboration?

Co-authorship in scientific research

Curriculum Lattes (CNPq)

Main system of curriculum information for the Brazilian

scientific community

Information is publicly available

But the process of data extraction and mining is complex

Scriptlattes (MENA-CHALCO et al, 2013)

Summary of database

Total of CVs Total of scientific publications

1.131.912 7.351.957

9

Identification of major knowledge areas (Scriptlattes)

Major Knowledge Areas (CNPq)

Engineering

Humanities

Applied Social Sciences

Linguistics, Letters and Arts

Agricultural Sciences

Exact and Earth Sciences

Health Sciences

Biological Sciences

Other areas

10

Identification of geographic location (Scriptlattes)

4.616 cities

11

Identification of co-authorship (Scriptlattes)

Author A; Author B. Impacts of... Revista XX , São Paulo. 2007.

Researcher A Researcher B

Author A; Author B. Impacts of .... Revista XX , São Paulo. 2007.

Similar titles

Coauthorship between researchers A and B

Bibliographical Production selected in CL

Articles in scientific journals

Expanded abstract published in proceedings of conferences

Book published/organized

Book chapter published

12

Full counting method

Researcher A

Researcher B

Researcher C Researcher D

Region X Region Y Region Z

Region X Region Y Region Z

Region X 1 2 2

Region Y 2 0 1

Region Z 2 1 0

Full counting method

Contains the total number of interregional co-authorships

(symmetric matrix)

Main diagonal: contains the total number of intraregional co-

authorships

Co-authorships associated to 1.347 Brazilian cities (dimension of

matrix)

⇒ 210 matrices of interregional co-authorships

by year (1990-2010) and major knowledge areas (9 + total)

13

Region X Region Y Region Z ... ... ... ... ...

Region X 1 2 2 ... ... ... ... ...

RegionY 2 0 1 ... ... ... ... ...

Region Z 2 1 0 ... ... ... ... ...

... ... ... ... . ...

... ... ... ... . ...

... ... ... ... . ...

... ... ... ... . ...

... ... ... ... ... ... ... ... ...

14

Scientific production in Brazil: 1992-1994

Scientific production measured by authorship in scientific publications

15

Scientific production in Brazil: 2007-2009

Scientific production measured by authorship in scientific publications

16

Location of public universities

17

Increase of scientific production by knowledge areas

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

I-II II-III III-IV IV-V V-VI

Engenharias

Ciências Humanas

Outros

Ciências Sociais Aplicadas

Linguística, Letras e Artes

Ciências Agrárias

Ciências Exatas e da Terra

Ciências da Saúde

Ciências Biológicas

Total

I - (1992-1994)

II - (1995-1997)

III - (1998-2000)

IV - (2001-2003)

V - (2004-2006)

VI - (2007-2009)

Gro

wth

rate

⇒ evidence of slowing-down of scientific production in Brazil

18

Spatial deconcentration

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1,0 26,0 51,0 76,0 101,0 126,0 151,0 176,0

1992-1994

1995-1997

1998-2000

2001-2003

2004-2006

2007-2009

Number of cities (ordered by individual production)

Pro

po

rtio

no

fto

tal

pro

duct

ion

90% of scientific production concentrated in

1992-1994 48 cities

2007-2009 102 cities

19

Knowledge flows in Brazil: 2007-2009

20

Scientific collaboration in Brazil

Total of Scientific Co-authorships

1992-1994 547.249

2007-2009 9.445.399

Main links in 2007-2009

Interregional links Intraregional links

Campinas/SP – São Paulo/SP 76.716 São Paulo/SP 1.343.394

Ribeirão Preto/SP – São Paulo/SP 74.078 Rio de Janeiro/RJ 630.049

Niterói/RJ – Rio de Janeiro/RJ 75.224 Porto Alegre/RS 393.888

Rio de Janeiro/RJ – São Paulo/SP 72.500 Belo Horizonte/MG 375.734

Seropédica/RJ – Rio de Janeiro/RJ 65.348 Ribeirão Preto/SP 278.218

Porto Alegre/RS – São Paulo/SP 47.343 Campinas/SP 212.248

21

Expansion of domestic scientific collaboration

0

200

400

600

800

1000

1200

1400

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

ENG HUM SOC LIN AGR EXA SAU BIO TOTAL

Nu

mb

ero

fci

ties

in t

he

net

wo

rks

22

Co-authorship network: Agricultural Sciences (1990 -2010)

Individual degree in the network

Capão do Leão/RS – Pelotas/RS 53.451Piracicaba/SP – Campinas/SP 30.695Lavras/MG – Viçosa/MG 29.334

Viçosa/MG 370.118São Paulo/SP 143.982Lavras/MG 143.559

23

Co-authorship network: Health Sciences (1990 -2010)

Individual degree in the network

Ribeirão Preto/SP – São Paulo/SP 95.120Campinas/SP – São Paulo/SP 78.023Rio de Janeiro/RJ – São Paulo/SP 66.852

São Paulo/SP 2.220.749Ribeirão Preto/SP 426.694Rio de Janeiro/RJ 388.479

Role of geographical proximity

Does space still matter for scientific interactions?

Did this effect decrease over time?

How to measure this effect?

Dimensions of proximity

Geographical, institutional, cognitive and social proximity

Dimensions occur together

24

Average Distance (for 105 main cities)

1992-1994 1995-1997 1998-2000 2001-2003 2004-2006 2007-2009

357,8 Km 387,6 Km 425,4 Km 490,5 Km 493,9 Km 465,2 Km

25

Spatial interaction modeling: Data

scientific collaborations between regions i and j

– measured by co-authorships in scientific publications

and : total of scientific publications in regions i and j

– measured by authorship in scientific publications

: geographical proximity between regions i and j

– measured by physical distance (Kilometres)

: institutional proximity between regions i and j

– dummy variable (1 if both regions have public universities)

26

Spatial interaction modeling for count data

Nature of data

Linear regressionmodel Count Data

Poisson model

Specification testIs there unobserved heterogeneity

(overdispersion)?

Negative binomial model

Specification test

Zero-inflatedNegative binomial

model (ZINB)

Negative binomial model

Specification test

Zero-inflatedPoisson model

(ZIP)Poisson model

27

Estimation results

1992-1994 1995-1997 1998-2000 2001-2003 2004-2006 2007-2009

Poisson

Origem – Destino (𝛼1 = 𝛼2) 0,8212714*** 0,7795005*** 0,8220109*** 0,7858146*** 0,7973171*** 0,7885987*** (0,0799382) (0,0678417) (0,0683882) (0,0579629) (0,054490) (0,0578959)

Distância Geográfica (𝛽1) -0,0019558*** -0,0019253*** -0,0017452*** -0,0015338*** -0,0015431*** -0,0017769*** (0,0003065) (0,0002531) (0,0002097) (0,0001606) (0,0001556) (0,0001774)

Distância Institucional (𝛽2) 0,3644302*** 0,4162181*** 0,1609404*** 0,3136939*** 0,2940121*** 0,4287121*** (0,176917) (0,1436342) (0,1254923) (0,1061115) (0,1068666) (0,1163698)

Constante (𝛼0) -7,857116*** -7,251477*** -7,874573*** -7,340407*** -7,597752*** -7,356414*** (1,304543) (1,149595) (1,215009) (1,060104) (1,034923) (1,116736)

Binomial Negativo

Origem – Destino (𝛼1 = 𝛼2) 0,8521451*** 0,8111029*** 0,7492518*** 0,7274424*** 0,7358830*** 0,6437665*** (0,0254626) (0,0215507) (0,0252036) (0,0219370) (0,0219320) (0,279855)

Distância Geográfica (𝛽1) -0,0008051*** -0,0008671*** -0,0007708*** -0,000797*** -0,0008311*** -0,0008877*** (0,0000654) (0,0000471) (0,0000387) (0,0000035) (0,000392) (0,000359)

Distância Institucional (𝛽2) 0,2046957*** 0,134085*** 0,2595981*** 0,1823897*** 0,0738276*** 0,2052725*** (0,0975923) (0,0765383) (0,0687016) (0,0634148) (0,0598206) (0,0589084)

Constante (𝛼0) -8,848608*** -8,256593*** -7,296663*** -6,709063*** -6,811066*** -5,024858*** (0,2523885) (0,2435624) (0,340571) (0,2793517) (0,3146031) (0,4536341)

Heterogeneidade (𝛼) 6,08251* 5,08992* 4,562474* 3,848097* 3,618955* 3,750808* (0,1914479) (0,116746) (0,0913702) (0,0664739) (0,0644162) (0,0666601)

Notas: i) 𝑛2=11.025 observações; ii) os erros-padrão estão entre parênteses; iii) ***, ** e * referem-se às estimativas

estatisticamente significantes aos níveis de significância de 0,001, 0,01 e 0,05, respectivamente.

28

Interpretation of the results

Characteristics of origin and destination regions

Positive and statistically significant

Institutional proximity

Positive and statistically significant

Geographical proximity

Negative and statistically significant

The value -0.0017769 means that for each additional 100

kilometers between two researchers, the probability for

collaboration decreases by about 16,3%, holding all other

variables constant

Effect is not linear: ↑ 300 Km (600 Km) ⇒ ↓ 41,3%

(65,6%) probability for collaboration

- Geographical distance still plays a crucial role

29

Results by knowledge areas

⇒ The effects of geographical distance on scientific networks are different

30

Conclusion

Overview of the evolution of scientific activity in Brazil (1990-2010)

Accelerated growth of scientific production and

collaboration

But there are evidences of slowdown

Spatial heterogeneity of scientific production

Knowledge flows are concentrated in the Southeast and

South regions

Evidence of spatial deconcentration of scientific production

and collaboration

Scientifically less traditional regions gained prominence

Role of geographical distance on scientific collaboration networks

Distance still plays a crucial role in determining the

intensity of knowledge flows

Effects varies between knowledge areas

31

Reference

The notes for this lecture were based on the following

paper:

“Scholarly Publication and Collaboration in Brazil: The

Role of Geography”

Sidone, O., Haddad, E. A. and Mena-Chalco, J. (2016)

Journal of The American Society for Information

Science and Technology

32

Questão

Em Tese de Doutorado defendida no IPE-USP no dia

24/11/2015, Ana Maria Bonomi Barufi concluiu que

“economias de aglomeração reforçam alguns dos

mecanismos que geram concentração espacial e

desigualdade regional”.

Discuta a conclusão da Dra. Barufi considerando

aspectos relacionados às preferências locacionais de

trabalhadores e firmas.

Código Ingresso Curso Nome P1 P2 Exercícios Subtotal

478424 2012/1 12051 Achiles Romero Riego 18.50 16.00 2.50 37.00

7929210 2011/2 12051 Amanda Amorim de Andrade

8557785 2013/1 12051 Amanda Broering Galvao Pereira 16.00 16.00 3.75 35.75

8071770 2013/1 12051 Andre Kamnitzer Bracco 20.00 18.00 5.00 43.00

8558059 2013/1 12051 Andreza Lopes da Silva 21.25 13.00 8.75 43.00

8012710 2012/1 12051 Bruno Hiromitsu Taba 17.50 21.00 5.00 43.50

8012679 2012/1 12051 Caio Madeira da Silva 22.00 15.00 8.75 45.75

8962526 2014/1 12051 Carlos Alberto Victorino Junior 19.25 12.00 11.25 42.50

8012901 2012/1 12051 Daniel Baracat de Freitas 25.25 10.00 6.25 41.50

7209054 2012/1 12051 Daniel Bomfim Hansen

8962613 2014/1 12051 Daniel Mariz de Oliveira Simantob 22.50 20.00 10.00 52.50

8479725 2013/1 12051 David Birmann 23.00 14.00 8.75 45.75

8138294 2013/1 12051 Edson Augusto Pereira de Moraes 19.50 16.00 8.75 44.25

8963295 2014/1 12051 Ernesto Assuncao França de Mello 18.75 25.00 11.25 55.00

8557997 2013/1 12051 Euler Santos de Sousa 20.50 16.00 5.00 41.50

8071554 2013/1 12051 Ezio Pontes de Souza Filho 20.50 18.00 2.50 41.00

8963580 2014/1 12051 Felipe Atilio Pinheiro Tredezini 15.00 9.00 10.00 34.00

8013301 2012/1 12051 Felipe Tank

8537222 2014/1 12051 Gabriel Marcondes dos Santos 16.50 15.00 10.00 41.50

8558063 2013/1 12051 Gabriela Martins Bueno 21.75 17.00 10.00 48.75

7663121 2012/1 12051 Gabrielle Carlos Paes 16.25 18.00 6.25 40.50

7699524 2012/1 12051 Geraldo Majela Damiao Nogueira 14.50 16.00 10.00 40.50

8012540 2012/1 12051 Giovana Mendonca Espinosa 15.50 10.00 6.25 31.75

8557451 2013/1 12051 Giovanna Abuhab Terezan 21.00 13.00 7.50 41.50

8479493 2013/1 12051 Guilherme de Lima Regio 16.50 13.00 11.25 40.75

4465389 2011/1 12051 Guilherme Neves de Oliveira 21.50 16.00 11.25 48.75

8012147 2012/1 12051 Guilherme Rodrigues da Silva 12.75 12.00 10.00 34.75

8801471 2014/1 12051 Guilherme Rodrigues Pereira 16.50 15.00 8.75 40.25

8016284 2012/1 12051 Heitor Antonio Ramos da Silva 21.00 14.00 7.50 42.50

8557635 2013/1 12051 Isabella Beck 14.50 8.00 10.00 32.50

8628766 2014/1 12051 Izabel Antunes Guarda Faez 26.00 24.00 11.25 61.25

6490631 2013/1 12051 Jefferson Lécio Leal 26.50 28.00 8.75 63.25

8557423 2013/1 12051 Joao Henrique Chalegra de Barros 14.00 12.00 7.50 33.50

9321978 2015/1 12051 Joao Luiz Goes Macedo Bicarato 14.50 8.00 6.25 28.75

7600047 2011/1 12051 Joseph da Silva Pavao Neto 22.00 26.00 3.75 51.75

8557962 2013/1 12051 Juliana Ferraz Salles Kesselring 19.50 18.00 10.00 47.50

4265921 2012/1 12051 Lucas Alvarenga Costa

8557486 2013/1 12051 Lucas da Cunha Rego Logiodice 4.00 10.00 0.00 14.00

8558574 2015/1 12051 Lucas da Silva Placides 13.50 14.00 6.25 33.75

8557826 2013/1 12051 Lucas Mendes Santos 17.25 19.00 8.75 45.00

7929203 2011/2 12051 Manuel Soares Duarte de Oliveira 23.50 23.00 6.25 52.75

8962871 2014/1 12051 Marcos Hernan Costa Manso Croce 13.00 16.00 10.00 39.00

8963207 2014/1 12051 Maria Alice da Silva Nunes 9.50 15.00 10.00 34.50

8139131 2013/1 12051 Mateus Calderam Villaca 20.50 21.00 6.25 47.75

4482660 2013/1 12051 Mathias Dahmer 13.50 16.00 11.25 40.75

8963465 2014/1 12051 Nicole Pitelli Biason 18.75 6.00 11.25 36.00

8479962 2013/1 12051 Otavio Cury Morello 23.75 23.00 8.75 55.50

6819779 2009/1 12051 Paulo Sergio Weber da Silva Bianchi 10.00 5.00 15.00

8558320 2013/1 12051 Pedro Davi Drugowick Ferreira 23.50 24.00 7.50 55.00

8963322 2014/1 12051 Pedro Ferreira Barchi 26.25 21.00 2.50 49.75

8071384 2012/1 12051 Pedro Uther Dantas Trajano

8012561 2012/1 12051 Rafael Angotti Miranda 10.00 15.00 7.50 32.50

8560452 2013/1 12051 Rafael Ferreira Caetano 15.75 8.00 2.50 26.25

8013350 2012/1 12051 Rafael Henrique de Meletti 16.25 17.00 7.50 40.75

8963743 2014/1 12051 Rafael Sammarco Branco Junior 19.75 24.50 11.25 55.50

8557382 2013/1 12051 Rebeca Junqueira Camillo de Carvalho 20.00 10.00 8.75 38.75

8014768 2013/1 12051 Richard Henrique Martins da Cunha 17.75 12.00 10.00 39.75

8963527 2014/1 12051 Santos Telfo Rojas Zegarrundo 12.00 11.00 11.25 34.25

8558208 2013/1 12051 Thais Haddad 22.75 21.00 8.75 52.50

8012130 2012/1 12051 Thiago Andrade Martiniano da Silva 6.50 14.00 5.00 25.50

8557569 2013/1 12051 Thomaz Lopes Macetti 16.25 13.00 2.50 31.75

8558282 2013/1 12051 Vinicius Querino Andraus 16.75 20.00 5.00 41.75

8963423 2014/1 12051 Vitor Fernandes Jaguanharo Carvalho 17.25 18.00 10.00 45.25

8557430 2013/1 12051 Viviane da Silva Dilly 18.50 11.00 7.50 37.00