Topic modelling through the bibliometrics lens and its technique 2025

Topic modelling (TM) is a significant natural language processing (NLP) task and is becoming more popular, especially, in the context of literature synthesis and analysis. Despite the growing volume of studies on the use of and versatility of TM, the knowledge of TM development, especially from the perspective of bibliometrics analysis is limited. To this end, this study evaluated TM research using two techniques namely, bibliometrics analysis and TM itself to provide the current status and the pathway for future studies in the TM field. For this purpose, this study used 16,941 documents collected from Scopus database from 2004 to 2023. Results indicate that the publications on TM have increased over the years, however, the citation impact has declined. Furthermore, the scientific production on TM is concentrated in two countries namely, China and the USA. Our findings showed there are several applications of TM that are understudied, for example, TM for image segmentation and classification. This paper highlighted the future research directions, most importantly, calls for increased multidisciplinary research approaches to fully deploy TM algorithms optimally and thus, increase usage in non-computer science subject areas.

Autores	Liu, Qian (58043907500); Yang, Shijie (59167076100); Chen, HeCheng (57203946435)
Título	Global trends and hotspots in the study of the effects of PM2.5 on ischemic stroke
Año	2024
DOI	10.1186/s41043-024-00622-3
Fuente	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202738639&doi=10.1186%2fs41043-024-00622-3&partnerID=40&md5=2f80b4bf91836970169230f4633fc742
Afiliaciones	Cerebrovascular Disease Department, Gansu Provincial Hospital, No.204 West Donggang Road, Gansu Province, Lanzhou, 730000, China; Key Laboratory of Cerebrovascular Disease of Gansu Province, Gansu Provincial Hospital, Gansu, Lanzhou, China; The First Clinical Medical College of Lanzhou University, Lanzhou, China
Tipo de acceso abierto	All Open Access; Gold Open Access
Referencia	Scopus
Artículo obtenido de:	Scopus

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Topic modelling through the bibliometrics lens and its technique

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