Vázquez-Tzompantzi, 2024

Dinámicas de colaboración científica de los graduados de doctorado del Instituto Politécnico Nacional en áreas disciplinarias

Dynamics of scientific collaboration of PhD graduates of the National Polytechnic Institute in disciplinary areas

Autor(es): Marisol Vázquez-Tzompantzi

Fuente: Mexican Journal of Technology and Engineering, Vol. 3, No. 3, pp. 12-23

DOI: https://doi.org/10.61767/mjte.003.3.1223

Resumen

El estudio analiza las redes de colaboración científica de investigadores que se graduaron de doctorado y destacaron académicamente en el Instituto Politécnico Nacional (IPN) durante el período 2012-2022. Su objetivo es conocer la estructura y la dinámica de las redes que han conformado estos graduados desde su consolidación como investigadores en las áreas de conocimiento dentro del instituto. La metodología empleada consiste en la recolección de datos de una de las bases institucionales del IPN y de la científica en este caso de Scopus, del análisis de redes utilizando el software R y su visualización de estas en Gephi. Las redes se dividen en las cuatro disciplinas de conocimiento ofertadas y se evalúan en términos de análisis de redes como nodos, aristas, comunidades detectadas, modularidad y grado promedio, lo que permite identificar patrones de colaboración y estructuras dentro de estas disciplinas científicas. Los resultados muestran que las redes generadas y analizadas presentan una alta modularidad y conectividad en comunidades bien definidas que facilitan la colaboración y el intercambio de conocimientos. Se observa que el área de Ciencias Médico Biológicas tiene una estructura altamente conectada y variada, mientras que otras áreas como la de Ingeniería y Ciencias Fisicomatemáticas presentan una modularidad más discreta. Las conclusiones validan que las redes de colaboración científica desempeñan un papel crucial en el fortalecimiento de la investigación y el intercambio de conocimiento, ofreciendo un marco de referencia para el diseño de nuevas y futuras políticas que promuevan la colaboración de venideros investigadores en el instituto.

Palabras clave: Redes de investigación, modularidad, comunidades, áreas de investigación, IPN.

Abstract

The study analyzes the scientific collaboration networks of researchers who graduated with a doctorate and stood out academically at the National Polytechnic Institute (IPN) during the period 2012-2022. Its objective is to know the structure and dynamics of the networks that these graduates have formed since their consolidation as researchers in the areas of knowledge within the institute. The methodology used consists of collecting data from one of the institutional databases of the IPN and the scientific database in this case from Scopus, network analysis using the R software and the visualization of these in Gephi. The networks are divided into the four knowledge disciplines offered and are evaluated in terms of network analysis such as nodes, edges, detected communities, modularity and average degree, which allows identifying collaboration patterns and structures within these scientific disciplines. The results show that the networks generated and analyzed present high modularity and connectivity in well-defined communities that facilitate collaboration and knowledge exchange. It is observed that the area of Medical Biological Sciences has a highly connected and varied structure, while other areas such as Engineering and Physic-Mathematical Sciences present a more discrete modularity. The conclusions validate that scientific collaboration networks play a crucial role in strengthening research and knowledge exchange, offering a framework for the design of new and future policies that promote the collaboration of future researchers at the Institute.

Keywords: Research networks, modularity, communities, research areas, IPN.

Referencias

Affonso, F., Santiago, M. D., & Rodrigues Dias, T. M. (2022). Análise da evolução de redes de colaboração científica para a predição de novas coautorias. Transinformação, 34, e200033. https://doi.org/10.1590/2318-0889202234e200033

Bai, X. M., Zhang, F. Liu J., & Xia, F. (2023). Quantifying the impact of scientific collaboration and papers via motif-based heterogeneous networks. Journal of Informetrics, 17(2). https://doi.org/10.1016/j.joi.2023.101397

Bulian, L., Cavar, I., & Mance, Z. (2022). “It’s dangerous to go alone!” Scientific excellence of PhD holders and their mentors – network analysis of Croatian doctoral students. Interdisciplinary Description of Complex Systems, 20(4), 483-499. https://doi.org/10.7906/indecs.20.4.12

Cárdenas, J., Ortega, J. L., & Fernández-Esquinas, M. (2024). Networks and innovation: enhancing the knowledge through a bibliometric network analysis. International Journal of Technology Management, 94(2). https://doi.org/10.1504/IJTM.2024.135712

Cardoso, T. M. L., Pinto, J. P., & Pestana, F. (2024). Networked research and open science: the WEIWER® experience. Educational Media International, 61(1-2), 16-25. https://doi.org/10.1080/09523987.2024.2357475

Fabila-Castillo, L. H., & Fabila-Monroy, R. (2023). Colaboración y Publicaciones Científicas en el Instituto Politécnico Nacional 1999-2019. Investigación Administrativa, 52(132). Instituto Politécnico Nacional, México.

Fuentes, M. G., Vásquez, H. C., Jarpa-Arriagada, C. G., & Muñoz, H. V. (2023). Teaching and learning processes of social work research. Perspectiva Educacional, 62(4), 157-178. https://doi.org/10.4151/07189729-Vol.62-Iss.4-Art.1287

IPN. (2022a). Instituto Politécnico Nacional. https://www.ipn.mx/comunidad/organizacion-y-estructura/mision-e-historia.html

IPN. (2022b). Instituto Politécnico Nacional. https://www.ipn.mx/oferta-educativa/posgrado/

Jung, H., Phoa, F. K. H., & Ashouri, M. (2022). A Leading Author Model for the Popularity Effect on Scientific Collaboration. Complex Networks & Their Applications, X(1), 424-437. https://doi.org/10.1007/978-3-030-93409-5_36

Lathabai, H. H., Nandy, A., & Singh, V. K. (2022). Institutional Collaboration Recommendation: An expertise-based framework using NLP and Network Analysis. Expert Systems with Applications, 118317. https://doi.org/10.1016/j.eswa.2022.118317

Li, H., Zhu, Y., & Niu, Y. (2022). Contact Tracing Research: A Literature Review Based on Scientific Collaboration Network. International Journal of Environmental Research and Public Health, 19(15), 9311. https://doi.org/10.3390/ijerph19159311

Liu, C. H., & Lin, J. Y. (2024). Collaboration-based scientific productivity: evidence from Nobel laureates. Scientometrics, 129(7), 3735-3768. https://doi.org/10.1007/s11192-024-05062-8

Marefat, R., & Khademi, R. (2022). Visualizing the scientific collaboration of nonlinear analysis in co-authorship: A scientometrics study. International Journal of Nonlinear Analysis and Applications, 1-9. http://dx.doi.org/10.22075/ijnaa.2022.21079.2229

Schmidt, C. M., Cielo, I. D., Sanches-Canevesi, F. C., & Cruz, R. W. D. (2022). Scientific collaboration networks in Secretarial field: an analysis among the researchers of ABPSEC. Revista de Gestão e Secretariado, 13(2), 172-200. https://doi.org/10.7769/gesec.v13i2.1289

Pei, R. M., Li, L. Q., Yang, Y. Y., & Zhou, Q. (2024). Co-evolution of international scientific mobility and international collaboration: a Scopus-based analysis. Scientometrics, 129(7), 4353-4378. https://doi.org/10.1007/s11192-024-05081-5

Ronda-Pupo, G. A. (2023). Mexico: A bridge in Cuba-US scientific collaboration. Scientometrics, 128(4), 2301-2315. https://doi.org/10.1007/s11192-023-04668-8

Vráblová, M., Bonetti, G., Henehan, G., Brown, R. E., Sykora, P., Marks, R. S., … & Tartaglia, G. M. (2024). Promoting International Scientific Cooperation: the Role of Scientific Societies. EuroBiotech Journal, 8(3), 115-121. https://doi.org/10.2478/ebtj-2024-0011

Zhai, L., & Yan, X. (2022). A directed collaboration network for exploring the order of scientific collaboration. Journal of Informetrics, 16, 101345. https://doi.org/10.1016/j.joi.2022.101345

Zhang, C., Feng, X., Li, Y., & Huan, Z. (2024). Scientific collaboration network structure and connectedness among the “Belt and Road” countries. Journal of Knowledge Economy. https://doi.org/10.1007/s13132-024-02078-6