A bibliometric analysis of topic modelling studies (2000–2017)

• Published in: Journal of information science Vol. 47; no. 2; pp. 161 - 175
• Main Authors: Li, Xin, Lei, Lei
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01-04-2021; Bowker-Saur Ltd
• Subjects: Bibliometrics; Data mining; Modelling; Social networks; Software engineering; Bibliometric analysis; Web of Science; topic modelling
• ISSN: 0165-5515; 1741-6485
• DOI: 10.1177/0165551519877049

Topic modelling is a powerful text mining tool that has been applied in many fields such as software engineering, political and linguistic sciences. To evaluate the development of topic modelling studies, the present study reports a bibliometric analysis of SCIE, SSCI and A&HCI listed articles published from 2000 and 2017. Bibliometric indices for productive authors, countries and institutions are analysed. In addition, thematic changes concerning topic modelling are also examined. Results show that China plays a leading role in this field. Topic modelling has established itself as an important technique in not only natural and formal sciences but also social sciences. LDA, social networks and text analysis are the topics with increasing popularity, while certain models (e.g. pLSA) and applications (e.g. topic detection) are declining in popularity. The findings could help researchers optimise research topic choices, seek collaboration with appropriate partners and stay up-to-date with the development of the field.