A Geographic Analysis of the Interdisciplinary Collaborations in the Brazilian Scientific Community

Authors

  • Geraldo J. Pessoa Junior Universidade Federal de Viçosa
  • Thiago M. R. Dias Centro Federal de Educação Tecnológica de Minas Gerais
  • Thiago H. P. Silva Universidade Tecnológica Federal do Paraná https://orcid.org/0000-0003-2990-5164
  • Alberto H. F. Laender Universidade Federal de Minas Gerais https://orcid.org/0000-0001-5032-2233

DOI:

https://doi.org/10.5753/jbcs.2022.2887

Keywords:

Interdisciplinary Collaborations, Coauthorship Networks, Scientific Communities, Geographic Analysis, Lattes Platform

Abstract

Interdisciplinary collaborations have recently attracted the attention of scholars, since they help bridging academic relationships and contribute to make scientific collaboration networks even stronger. However, previous works on this subject have mainly focused on characterizing such interdisciplinary collaborations in specific research groups or scientific communities. In this article, we start from a previous work in which we characterized the interdisciplinary collaborations within the entire Brazilian scientific community, as defined according to the upper level of the knowledge area classification scheme proposed by CNPq, the Brazilian National Council for Scientific and Technological Development, considering the following eight major areas: Agrarian Sciences, Applied and Social Sciences, Biological Sciences, Engineering, Exact and Earth Sciences, Health Sciences, Humanities, and Linguistics, Letters and Arts. Based on this interdisciplinary collaboration network, we conducted a geographic analysis that characterizes how these collaborations have been spread across the Brazilian geographic regions. Overall, our results show strong collaborative ties involving the triad formed by the three main Brazilian geographic regions (Southeast, South and Northeast) for all major areas. Besides, three of the eight major areas (Agrarian Sciences, Biological Sciences, and Health Sciences) show a massive participation in interdisciplinary collaborations across all regions. Despite that, geographic proximity is an important factor, since the proportion of interdisciplinary collaborations involving researchers from the same region is high. Finally, we analyze the patterns of interdisciplinary collaboration by regions and by major areas, thus showing that the Brazilian interdisciplinary network is highly connected.

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References

Abramo, G., D’Angelo, C. A., and Di Costa, F. (2018). The effect of multidisciplinary collaborations on research diversification. Scientometrics, 116(1):423–433.

Adams, J. D., Black, G. C., Clemmons, J. R., and Stephan, P. E. (2005). Scientific teams and institutional collaborations: Evidence from U.S. universities, 1981–1999. Research Policy, 34(3):259–285.

Chiarini, T., Oliveira, V. P., and do Couto e Silva Neto, F. C. (2014). Spatial distribution of scientific activities: An exploratory analysis of brazil, 2000–10. Science and Public Policy, 41(5):625–640.

de Siqueira, G. O., Canuto, S. D., Gonçalves, M. A., and Laender, A. H. F. (2020). A pragmatic approach to hierarchical categorization of research expertise in the presence of scarce information. International Journal on Digital Libraries, 21(1):61–73.

Dias, T. M. R. and Moita, G. F. (2015). A method for the identification of collaboration in large scientific databases. Em Questão, 21(2).

Dornbusch, F., von Proff, S., and Brenner, T. (2013). The organizational and regional determinants of inter-regional collaborations-academic inventors as bridging agents. Technical report, Working Papers on Innovation and Space.

Freire, V. P. and Figueiredo, D. R. (2011). Ranking in collaboration networks using a group based metric. Journal of the Brazilian Computer Society, 17(4):255–266.

Furtado, C. A., Davis Jr, C. A., Gonçalves, M. A., and de Almeida, J. M. (2015). A Spatiotemporal Analysis of Brazilian Science from the Perspective of Researchers’ Career Trajectories. PloS One, 10(10):e0141528.

Garay, Y., Akbar, M., and Gates, A. Q. (2016). Towards Identifying Potential Research Collaborations from Scientific Research Networks using Scholarly Data. In Proceedings of the 16th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2016, Newark, NJ, USA, June 19 - 23, 2016, pages 217–218.

Haythornthwaite, C. (2006). Learning and knowledge networks in interdisciplinary collaborations. Journal of the American Society for Information Science and Technology, 57(8):1079–1092.

Hoekman, J., Frenken, K., and Tijssen, R. J. (2010). Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe. Research Policy, 39(5):662–673.

Hua, G. and Haughton, D. (2012). A network analysis of an online expertise sharing community. Social Network Analysis and Mining, 2(4):291–303.

Huang, M.-H. and Chang, Y.-W. (2011). A study of interdisciplinarity in information science: Using direct citation and co-authorship analysis. Journal of Information Science, 37(4):369–378.

Iglič, H., Doreian, P., Kronegger, L., and Ferligoj, A. (2017). With whom do researchers collaborate and why? Scientometrics, 112(1):153–174.

Jiang, J., Shi, P., An, B., Yu, J., and Wang, C. (2017). Measuring the social influences of scientist groups based on multiple types of collaboration relations. Information Processing & Management, 53(1):1–20.

Jones, B. F., Wuchty, S., and Uzzi, B. (2008). Multi-University Research Teams: Shifting Impact, Geography, and Stratification in Science. Science, 322(5905):1259–1262.

Kato, M. and Ando, A. (2013). The relationship between research performance and international collaboration in chemistry. Scientometrics, 97(3):535–553.

Kulbacki, M., Segen, J., Knieć, W., Klempous, R., Kluwak, K., Nikodem, J., Kulbacka, J., and Serester, A. (2018). Survey of drones for agriculture automation from planting to harvest. In 2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES), pages 000353–000358. IEEE.

Leão, J. C., Brandão, M. A., de Melo, P. O. S. V., and Laender, A. H. F. (2018). Who is really in my social circle? - Mining social relationships to improve detection of real communities. Journal of Internet Services and Applications, 9(1):20:1–20:17.

Leydesdorff, L. and Persson, O. (2010). Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes. Journal of the American Society for information Science and Technology, 61(8):1622–1634.

Li, Q., Brown, J. B., Huang, H., Bickel, P. J., et al. (2011). Measuring reproducibility of high-throughput experiments. The annals of applied statistics, 5(3):1752–1779.

Lima et al., H. (2013). Aggregating Productivity Indices for Ranking Researchers Across Multiple Areas. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL’13, Indianapolis, IN, USA, July 22 - 26, 2013, pages 97–106.

Liu, X., Bollen, J., Nelson, M. L., and Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, 41(6):1462–1480.

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 Technology, 65(7):1424–1445.

Mooney, H. A., Duraiappah, A., and Larigauderie, A. (2013). Evolution of natural and social science interactions in global change research programs. Proceedings of the National Academy of Sciences, 110(Supplement 1):3665–3672.

Morillo, F., Bordons, M., and Gómez, I. (2003). Interdisciplinarity in science: A tentative typology of disciplines and research areas. Journal of the American Society for Information Science and Technology, 54(13):1237–1249. Newman, M. (2003). Mixing patterns in networks. Physical Review E, 67(026126).

Pan, R. K., Kaski, K., and Fortunato, S. (2012). World citation and collaboration networks: uncovering the role of geography in science. Scientific reports, 2:902.

Peet, R. K. (1975). Relative diversity indices. Ecology, 56(2):496–498.

Pessoa Junior, G. J., Dias, T. M., Silva, T. H., and Laender, A. H. (2020). On interdisciplinary collaborations in scientific coauthorship networks: the case of the Brazilian community. Scientometrics, 124(3):2341–2360.

Pessoa Junior, G. J., Dias, T. M. R., Silva, T. H. P., and Laender, A. H. F. (2019). Interdisciplinary Collaborations in the Brazilian Scientific Community. In Digital Libraries for Open Knowledge - 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, Sept. 9-12, 2019, Proceedings, pages 145–153.

Porter, A. L., Roessner, D. J., and Heberger, A. E. (2008). How interdisciplinary is a given body of research? Research evaluation, 17(4):273–282.

Shi, S., Zhang, W., Zhang, S., and Chen, J. (2018). Does prestige dimension influence the interdisciplinary performance of scientific entities in knowledge flow? Evidence from the e-government field. Scientometrics, 117(2):1237–1264.

Sidone, O. J. G., Haddad, E. A., and Mena-Chalco, J. P. (2017). Scholarly publication and collaboration in Brazil: The role of geography. Journal of the Association for Information Science and Technology, 68(1):243–258.

Silva, F. N., Rodrigues, F. A., Jr., O. N. O., and da F. Costa, L. (2013). Quantifying the interdisciplinarity of scientific journals and fields. J. Informetrics, 7(2):469–477.

Silva, T. H. P., Laender, A. H. F., Davis, C. A., da Silva, A. P. C., and Moro, M. M. (2017). A profile analysis of the top Brazilian Computer Science graduate programs. Scientometrics, 113(1):237–255.

Silva, T. H. P., Laender, A. H. F., Davis Jr, C. A., da Silva, A. P. C., and Moro, M. M. (2016). The Impact of Academic Mobility on the Quality of Graduate Programs. D-Lib Magazine, 22(9/10).

Silva, T. H. P., Laender, A. H. F., and Vaz de Melo, P. O. S. (2019). Characterizing Knowledge-Transfer Relationships in Dynamic Attributed Networks. In IEEE/ACM 2019 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, Vancouver, Canada, August 28-31, 2019, pages 234–241.

Sonnenwald, D. H. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41(1):643–681.

Wagner, C., Staheli, L., Silberglitt, R., Wong, A., and Kadtke, J. (2002). Linking effectively: Learning lessons from successful collaboration in science and technology. RAND’s Science & Technology Policy Institute.

Wilsdon, J. et al. (2011). Knowledge, networks and nations: Global scientific collaboration in the 21st century. The Royal Society.

Yan, E., Ding, Y., and Sugimoto, C. R. (2011). P-rank: An indicator measuring prestige in heterogeneous scholarly networks. Journal of the American Society for Information Science and Technology, 62(3):467–477.

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Published

2022-09-22

How to Cite

Pessoa Junior, G. J., M. R. Dias, T., H. P. Silva, T., & H. F. Laender, A. (2022). A Geographic Analysis of the Interdisciplinary Collaborations in the Brazilian Scientific Community. Journal of the Brazilian Computer Society, 28(1), 1–12. https://doi.org/10.5753/jbcs.2022.2887

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