Metodologia orientada a ciência de dados em grafos para avaliação de PPGs

Breno Santana Santos; Ivanovitch Silva; Elvis Melo

doi:10.20906/sbai.v1i1.2838

Breno Santana Santos Programa de Pós-Graduação em Engenharia Elétrica e de Computação, Universidade Federal do Rio Grande do Norte, RN, Natal e Universidade Federal de Sergipe, SE, Itabaiana
Ivanovitch Silva Programa de Pós-Graduação em Engenharia Elétrica e de Computação, Universidade Federal do Rio Grande do Norte, RN, Natal
Elvis Melo Programa de Pós-Graduação em Engenharia Elétrica e de Computação, Universidade Federal do Rio Grande do Norte, RN, Natal

DOI: https://doi.org/10.20906/sbai.v1i1.2838

Keywords: Data Science, Complex Network Analysis, Machine Learning, Post-Graduate Programs, Scientometrics, Bibliometrics

Abstract

The mapping and analysis of scientific knowledge makes it possible to identify the dynamics and/or growth of a particular research field or to support strategic decisions related to different research entities, based on bibliometric and/or scientometric indicators. However, with the exponential growth of scientific production, a systematic and data-oriented approach to the analysis of this large set of scientific data becomes increasingly essential. Thus, in this work, a data-oriented methodology was proposed, combining techniques of Machine Learning and Complex Network Analysis, for the extraction of implicit knowledge in scientific production bases, in addition to its validation through a study of case in the Brazilian Engineering IV. The results suggest the feasibility of the proposal, indicating the main researchers, prominent areas and partnership networks. Therefore, the proposed methodology has the potential to implement and expand strategic and proactive decisions of post-graduate programs aiming for a growing impact on society.