Researchers concentrate their efforts to understand the different female relations with science, using approaches that review their scientific and technological participation, as well as, seeking to understand their academic trajectory and performance. In this context, this study aimed to analyze the participation of women using as database the set of PhD graduates who have their curricula entered in the Lattes Platform. The data were collected and selected obtaining a set of 125,515 curricula of women who had completed their PhD. The PhD data were grouped according to the large areas of expertise (fields of science) and academic training, in which it was possible to analyze the academic evolution and the scientific and technological production of the group in a temporal manner. The different types of studies that help to understand the general aspect of women active mainly in science, besides being relevant, exhibit the characteristics of their research. This may be useful for the generation of national scientific indicators, for the management of information in the scientific area and for technological development. It is also useful to encourage and valuate participation of women in science.
Gênero é um termo abrangente que tem gerado muitos estudos e esforços de diversas áreas, a fim de ampliar as abordagens e perspectivas sobre o tema. O estudo aqui apresentado serve a diversos propósitos, como direcionar o fomento à pesquisa e compreender a importância que o domínio gênero demanda sobre o cenário da ciência. Logo, o objetivo deste trabalho é caracterizar e analisar com ênfase em gênero o conjunto de doutores com currículos cadastrados na Plataforma Lattes. Para isso, após a aquisição dos dados curriculares do conjunto de doutores, aplica-se técnica computacional de mineração de texto para identificar o gênero da palavra através do primeiro nome do pesquisador. Esta técnica utiliza-se de uma tabela contendo 608 sufixos distribuídos entre cada letra do alfabeto, que é consultada através da última letra do nome do indivíduo a ser identificado, verificando se existe sufixo correspondente ao inverso do nome sem a última letra. A identificação de gênero do conjunto de doutores possibilitou caracterizar de modo geral, constatando, conforme esperado, um cenário com maioria masculina em 53,07% e feminina com 46,93%. Os resultados apresentados mostram uma caracterização geral do conjunto e podem auxiliar no entendimento sobre o domínio gênero no desenvolvimento da ciência brasileira.
When publishing an article with other authors, initial links must be formed by a collaboration between authors, a scientific collaboration network. In this context, the papers are represented by the edges, and the authors are represented the nodes, forming a network. At this moment, the following question arises: How does the evolution of the network occur over time? Understanding what factors are essential for creating a new connection to answer this question is necessary. Therefore, the purpose of this article is to foresee connections in co-authorship networks formed by PhDs with curricula registered in Lattes Platform in the areas of Information Sciences and Biology. The following steps are performed: initially the data is extracted and organized. This step is essential for the continuity of the process. Then, co-authorship networks are generated based on articles published together. Subsequently, the attributes to be used are defined and some metrics are calculated. Finally, machine learning algorithms estimate future scientific collaborations in the selected areas. The Lattes Platform has 6.6 million resumes for researchers and represents one of the most relevant and recognized scientific repositories worldwide. As a result, random forest and logistic regression algorithms showed the highest hit rates, and preferential attachment attribute was identified as the most influential in the emergence of new scientific collaborations. Through the results, it is possible to establish the evolution of the network of scientific associations of researchers at a national level, assisting development agencies in selecting of future outstanding researchers.
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