Network Analysis and Natural Language Processing to Obtain a Landscape of the Scientific Literature on Materials Applications.
ACS Appl Mater Interfaces
; 15(23): 27437-27446, 2023 Jun 14.
Article
em En
| MEDLINE
| ID: mdl-37270838
Recent progress in natural language processing (NLP) enables mining the literature in various tasks akin to knowledge discovery. Obtaining an updated birds-eye view of key research topics and their evolution in a vast, dynamic field such as materials science is challenging even for experienced researchers. In this Perspective paper, we present a landscape of the area of applied materials in selected representative journals based on a combination of methods from network science and simple NLP strategies. We found a predominance of energy-related materials, e.g., for batteries and catalysis, organic electronics, which include flexible sensors and flexible electronics, and nanomedicine with various topics of materials used in diagnosis and therapy. As for the impact calculated through standard metrics of impact factor, energy-related materials and organic electronics are again top of the list across different journals, while work in nanomedicine has been found to have a lower impact in the journals analyzed. The adequacy of the approach to identify key research topics in materials applications was verified indirectly by comparing the topics identified in journals with diverse scopes, including journals that are not specific to materials. The approach can be employed to obtain a fast overview of a given field from the papers published in related scientific journals, which can be adapted or extended to any research area.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
ACS Appl Mater Interfaces
Assunto da revista:
BIOTECNOLOGIA
/
ENGENHARIA BIOMEDICA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Estados Unidos