Assessing the evolution of research topics in a biological field using plant science as an example.
PLoS Biol
; 22(5): e3002612, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38781246
ABSTRACT
Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field. Using plant biology as an example, we used machine learning and language models to classify plant science citations into topics representing interconnected, evolving subfields. The changes in prevalence of topical records over the last 50 years reflect shifts in major research trends and recent radiation of new topics, as well as turnover of model species and vastly different plant science research trajectories among countries. Our approaches readily summarize the topical diversity and evolution of a scientific field with hundreds of thousands of relevant papers, and they can be applied broadly to other fields.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Plantas
Idioma:
En
Revista:
PLoS Biol
Asunto de la revista:
BIOLOGIA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos