The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling

Autor(es)

Prati, Ronaldo C. ; Rodrigues, Bruno S. M. ; Aragao, Iberis ; Soares, Thereza A. ; Quiles, Marcos G. ; Da Silva, Juarez L. F.

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF CHEMICAL INFORMATION AND MODELING; v. 64, n. 4, p. 5-pg., 2024-02-12.

Resumo

There has been a growing recognition of the need for diversity and inclusion in scientific fields. This trend is reflected in the Journal of Chemical Information and Modeling (JCIM), where there has been a gradual increase in the number of papers that embrace this diversity. In this viewpoint, we analyze the evolution of the profile of papers published in JCIM from 1996 to 2022 addressing three diversity criteria, namely interdisciplinarity, geographic and gender distributions, and their impact on citation patterns. We used natural language processing tools for the classification of main areas and gender, as well as metadata, to analyze a total of 7384 articles published in the categories of research articles, reviews, and brief reports. Our analyses reveal that the relative number of articles and citation patterns are similar across the main areas within the scope of JCIM, and international collaboration and publications encompassing two to three research areas attract more citations. The percentage of female authors has increased from 1996 (less than 20%) to 2022 (more than 32%), indicating a positive trend toward gender diversity in almost all geographic regions, although the percentage of publications by single female authors remains lower than 20%. Most JCIM citations come from Europe and the Americas, with a tendency for JCIM papers to cite articles from the same continent. Furthermore, there is a correlation between the gender of the authors, as JCIM manuscripts authored by females are more likely to be cited by other JCIM manuscripts authored by females. (AU)

• Processo FAPESP: 22/09285-7 - Exploração do espaço químico via aprendizado semissupervisionado para geração de novos materiais
• Beneficiário: Marcos Gonçalves Quiles
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/11631-2 - CINE: desenvolvimento computacional de materiais utilizando simulações atomísticas, meso-escala, multi-física e inteligência artificial para aplicações energéticas
• Beneficiário: Juarez Lopes Ferreira da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Programa Centros de Pesquisa em Engenharia
• Processo FAPESP: 18/21401-7 - EMU concedido no processo 2017/11631-2: cluster computacional de alto desempenho - ENIAC
• Beneficiário: Juarez Lopes Ferreira da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
• Processo FAPESP: 21/04283-3 - Uma abordagem de múltipla resolução para o polimorfismo de agregados lipopolissacarídicos induzido por metais
• Beneficiário: Thereza Amélia Soares da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular