Exploring the knowledge domain of earthquake prediction based on bibliometric analysis and text mining

Article type: Research Article

Authors: He, Xiaorong^{; *}

Affiliations: School of Information Engineering, Nanjing Audit University, Nanjing, Jiangsu, China

Correspondence: [*] Correspondence to: Xiaorong He, School of Information Engineering, Nanjing Audit University, Nanjing, Jiangsu 211815, China. E-mail: [email protected].

Abstract: Earthquake prediction is one of the important themes of earthquake research, and it is also a very difficult scientific problem in the world. In this study, a bibliometric analysis is conducted on the scientific publications about earthquake prediction indexed in SCIE (Science Citation Index Expanded) and SSCI (Social Sciences Citation Index) databases during the past two decades (1998–2017). The subject categories, annual and journal distributions, leading countries/regions and institutions are investigated in this field. The main research topics are identified through text mining method. The research trends are explored by keyword co-occurrence analysis and bursting keywords detection techniques. The results of this study are helpful for scholars in this field to find the knowledge structure and important participants. It is also helpful for scholars to seize the current research hotspots and future development trends in this field.

Keywords: Earthquake prediction, visualization, bibliometric analysis, citation structure, research trends

DOI: 10.3233/JIFS-212442

Journal: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5885-5901, 2022