Brazilian network of PhDs working with probability and statistics. (English) Zbl 1404.62147

Digiampietri, Luciano; Rêgo, Leandro; De Souza, Filipe Costa; Ospina, Raydonal; Mena-Chalco, Jesús

Braz. J. Probab. Stat. 32, No. 4, 755-782 (2018).

Summary: Statistical and probabilistic reasoning enlightens our judgments about uncertainty and the chance or beliefs on the occurrence of random events in everyday life. Therefore, there are scientists working with Probability and Statistics in various fields of knowledge, what favors the formation of scientific network collaborations of researchers with different backgrounds. Here, we propose to describe the Brazilian PhDs who work with probability and statistics. In particular, we analyze national and states collaboration networks of such researchers by calculating different metrics. We show that there is a greater concentration of nodes in and around the cites which host Probability and Statistics graduate programs. Moreover, the states that host P&S Doctoral programs are the most central. We also observe a disparity in the size of the states networks. The clustering coefficient of the national network suggests that this network and regional differences especially with respect to states from South-east and North is not cohesive and, probably, it is in a maturing stage.

MSC:

62P25	Applications of statistics to social sciences
62H12	Estimation in multivariate analysis
91D30	Social networks; opinion dynamics

Keywords:

academic collaboration; CNPq’s productivity research fellows; probability and statistics; social network analysis

Software:

scriptLattes

References:

[1]	Abbasi, A., Altmann, J. and Hossain, L. (2011). Identifying the effecs of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance mesuares and social network analysis mesuares. Journal of Informetrics5, 594–607.
[2]	Alves, A. D., Yanasse, H. H. and Soma, N. Y. (2014). Perfil dos bolsistas PQ da Área de Química baseado na Plataforma lattes. Química Nova37, 377–383.
[3]	Andretta, P. I. (2012). Uma análise sobre a produção, produtividade e colaboração na ciência da informação no Brasil entre os anos 2007 a 2009. Palabra Clave1, 48–52.
[4]	Andretta, P. I., Silva, E. and Ramos, R. (2012). Aproximações sobre produção, produtividade e colaboração científica entre os departamentos de ciência da informação do estado de São Paulo. RDBCI9, 46–63.
[5]	Ara, A. and Louzada, F. (2012). Descrição de algumas das dimensões que compõem o perfil do corpo docente dos departamentos de estatística do Brasil. Boletim de Educação Matemática26(42A), 23–38.
[6]	Arruda, D., Bezerra, F., Neris, V., Rocha De Toro, P. and Wainera, J. (2009). Brazilian computer science research: Gender and regional distributions. Scientometrics79, 651–665.
[7]	Baccini, A., Barabesi, L. and Marcheselli, M. (2009). How are statistical journals linked? A network analysis. Chance22, 35–45.
[8]	Bellotti, E. (2012). Getting funded. Multi-level network of physicists in Italy. Social Networks34, 215–229.
[9]	Bojanowski, M. and Corten, R. (2014). Measuring segregation in social networks. Social Networks39, 14–32.
[10]	Bonacich, P. and Lloyd, P. (2001). Eigenvector-like measures of centrality for asymmetric relations. Social Networks23, 191–201.
[11]	Bordons, M., Aparicio, J., González-Albo, B. and Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of Informetrics9, 135–144.
[12]	Cimenler, O., Reeves, K. A. and Skvoretz, J. (2014). A regression analysis of researchers’ social network metrics on their citation performance in college of engineering. Journal of Informetrics8, 667–682.
[13]	Costa, B. M. G., da Silva Pedro, E. and de Macedo, G. R. (2013). Scientific collaboration in biotechnology: The case of the northeast region in Brazil. Scientometrics95, 571–592.
[14]	de Arruda, G. F., Peron, T. K. D., de Andrade, M. G., Achcar, J. A. and Rodrigues, F. A. (2013). The influence of network properties on the synchronization of Kuramoto oscillators quantified by a Bayesian regression analysis. Journal of Statistical Physics152, 519–533.
[15]	De Stefano, D., Giordano, G. and Vitale, M. P. (2011). Issues in the analysis of co-authorship networks. Quality and Quantity45, 1091–1107.
[16]	Digiampietri, L., Mena-Chalco, J., Silva, G. S., Oliveira, L., Malheiro, A. and Meira, D. (2012). Dinâmica das relações de coautoria nos programas de pós-graduação em computação no Brasil. In I Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2012).
[17]	Digiampietri, L. A. and da Silva, E. E. (2011). A framework for social network of researchers analysis. Iberoamerican Journal of Applied Computing1, 1–24.
[18]	Digiampietri, L. A., Mena-Chalco, J. P., Melo, P. O. V., Malheiros, A. P., Meira, D. N. O., Franco, L. F. and Oliveira, L. B. (2014). BraX-ray: An X-ray of the Brazilian computer science graduate programs. PLoS ONE9, 20. DOI:10.1371/journal.pone.0094541.
[19]	Easley, D. and Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge, MA: Cambridge University Press. · Zbl 1205.91007
[20]	Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks1, 215–239.
[21]	Glänzel, W. and Schubert, A. (2005) Handbook of Quantitative Science and Technology Research: The Use of Publication and Patent Statistics in Studies of S&T Systems, Chapter Analysing Scientific Networks Through Co-Authorship, 257–276. Dordrecht: Springer.
[22]	Jackson, M. O. (2008). Social and Economic Networks. Princeton, NJ: Princeton University Press. · Zbl 1149.91051
[23]	Katz, J. S. and Martin, B. R. (1997). What is research collaboration? Research Policy26, 1–18.
[24]	Krackhardt, D. and Stern, R. (1988). Informal networks and organizational crises: An experimental simulation. Social Psychology Quarterly51, 123–140.
[25]	Latapy, M., Magnien, C. and Vecchio, N. D. (2008). Basic notions for the analysis of large two-mode networks. Social Networks30, 31–48.
[26]	Mählck, P. and Persson, O. (2000). Socio-bibliometric mapping of intra-departmental networks. Scientometrics49, 81–91. DOI:10.1023/A:1005661208810.
[27]	Melin, G. and Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics36, 363–377.
[28]	Mena-Chalco, J. P., Digiampietri, L. A. and Cesar Jr., R. M. (2012). Caracterizando as redes de coautoria de currículos Lattes. In Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2012).
[29]	Mena-Chalco, J. P. and Cesar Jr., R. M. (2009). scriptLattes: An open-source knowledge extraction system from the lattes platform. Journal of the Brazilian Computer Society15, 31–39.
[30]	Mena-Chalco, J. P., Digiampietri, L. A., Lopes, F. M. and Cesar, R. M. (2014). Brazilian bibliometric coauthorship networks. Journal of the Association for Information Science and Technology65, 1424–1445.
[31]	Milgram, S. (1967). The small world problem. Psychology Today2, 60–67.
[32]	Nascimento, S. and Beuren, I. M. (2011). Redes sociais na produção científica dos programas de pós-graduação de ciências contábeis do Brasil. Revista de Administração Contemporânea15, 47–66.
[33]	Neal, Z. (2014). The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks39, 84–97.
[34]	Newman, M. E. J. (2001). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics64, 016131.
[35]	Newman, M. E. J. and Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics69, 026113.
[36]	Peron, T. K. D., Costa, L. d. F. and Rodrigues, F. A. (2012). The structure and resilience of financial market networks. Chaos22, 013117. · Zbl 1331.37144 · doi:10.1063/1.3683467
[37]	Said, Y. H., Wegman, E. J. and Sharabati, W. K. (2010). Author-coauthor social networks and emerging scientific subfields. In Data Analysis and Classification: From Exploration to Confirmation. Stud. Classification Data Anal. Knowledge Organ. 257–268. Berlin: Springer.
[38]	Senra, N. (2008). Pesquisa histórica das estatísticas: Temas e fontes. História, Ciências, Saúde15, 411–425.
[39]	Senra, N. (2009). Na Primeira República, Bulhões Carvalho legaliza a atividade estatística e a põe na ordem do Estado. Boletim do Museu Paraense Emilio Goeldi. Ciências Humanas4, 387–399. DOI:10.1590/S1981-81222009000300003.
[40]	Stefano, D. D., Fuccella, V., Vitale, M. P. and Zaccarin, S. (2013). The use of different data sources in the analysis of co-authorship networks and scientific performance. Social Networks35, 370–381.
[41]	Travers, J. and Milgram, S. (1969). An experimental study of the small world problem. Sociometry32, 425–443. DOI:10.2307/2786545.
[42]	Wasserman, S. and Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge, MA: Cambridge University Press. · Zbl 0926.91066
[43]	Yoshikane, F. and Kageura, K. (2004). Comparative analysis of coauthorship networks of different domains: The growth and change of networks. Scientometrics60, 435–446.
[44]	Yousefi-Nooraie, R., Akbari-Kamrani, M., Hanneman, R. A. and Etemadi, A. (2008). Association between co-authorship network and scientific productivity and impact indicators in academic medical research centers: A case study in Iran. Health Research Policy and Systems6, 1–8.