Bibliometric Analysis of Literature on Inverse Problems in Geophysics Using CiteSpace

Abstract Purpose Research on inverse problems of geophysics is extensive. Thus, there is a need to conduct in-depth and comprehensive bibliometric research to capture the overall development of the field. Design/methodology/approach We conduct a bibliometric analysis using CiteSpace to reveal dynamic trends in collaboration, co-citation, and co-occurrence in this field. Findings We find that publications in the field have shown a fluctuating upward trend since 2004, accompanied by a gradual increase in its proportion within the broader geophysics’ literature. In terms of institutional collaborations, Chinese and French research institutions occupy an important position in the global collaboration network. From a co-citation perspective, Geophysics is the most cited journal, and Araya-Polo Mauricio’s article (Araya-Polo, M., J. Jennings, A. Adler, and T. Dahlke. 2018. “Deep-Learning Tomography.” The Leading Edge 37 (1): 58–66) is the most cited reference. From the perspective of keyword co-occurrence, the keyword clusters show the diversity of geophysical inversion research. The research topics cover fundamental theory, method development, and practical applications. In addition, future research may focus more on research based on data-driven workflows and artificial intelligence. Research limitations Only the SCI and SSCI editions in the Web of Science database were used as the data source, ignoring the literature in other databases. We focused on the literature from 2004 to 2023, which excludes the latest literature in 2024 and earlier literature before 2004. Practical implications We provided a comprehensive and specific analysis of the literature in the field over the last 20 years to help readers gain a comprehensive understanding of the current state of research, hotspots, evolution, and trends in the field. We discussed current research challenges and possible future research directions to help researchers identify appropriate research directions and conduct subsequent research more efficiently. Originality/value Compared with previous related studies, this study is innovative as we provide a comprehensive and specific analysis of the literature in the field over the last 20 years to help readers gain a comprehensive understanding of the current state of research, hotspots, evolution, and trends in the field and discuss current research challenges and possible future research directions to help researchers identify appropriate research directions and conduct subsequent research more efficiently.

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Publication Details

Journal
Journal of Data and Information Science
Published
2026-07-17
DOI
https://doi.org/10.1515/jdis-2025-0464
Primary Topic
Geophysical and Geoelectrical Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Bibliometric Analysis of Literature on Inverse Problems in Geophysics Using CiteSpace

Robin Haunschild, Jiajia Liu, Hanyue Sun
Journal of Data and Information Science
Geophysical and Geoelectrical Methods
article

Bibliometric Analysis of Literature on Inverse Problems in Geophysics Using CiteSpace

Robin Haunschild, Jiajia Liu, Hanyue Sun
article en

Abstract

Abstract Purpose Research on inverse problems of geophysics is extensive. Thus, there is a need to conduct in-depth and comprehensive bibliometric research to capture the overall development of the field. Design/methodology/approach We conduct a bibliometric analysis using CiteSpace to reveal dynamic trends in collaboration, co-citation, and co-occurrence in this field. Findings We find that publications in the field have shown a fluctuating upward trend since 2004, accompanied by a gradual increase in its proportion within the broader geophysics’ literature. In terms of institutional collaborations, Chinese and French research institutions occupy an important position in the global collaboration network. From a co-citation perspective, Geophysics is the most cited journal, and Araya-Polo Mauricio’s article (Araya-Polo, M., J. Jennings, A. Adler, and T. Dahlke. 2018. “Deep-Learning Tomography.” The Leading Edge 37 (1): 58–66) is the most cited reference. From the perspective of keyword co-occurrence, the keyword clusters show the diversity of geophysical inversion research. The research topics cover fundamental theory, method development, and practical applications. In addition, future research may focus more on research based on data-driven workflows and artificial intelligence. Research limitations Only the SCI and SSCI editions in the Web of Science database were used as the data source, ignoring the literature in other databases. We focused on the literature from 2004 to 2023, which excludes the latest literature in 2024 and earlier literature before 2004. Practical implications We provided a comprehensive and specific analysis of the literature in the field over the last 20 years to help readers gain a comprehensive understanding of the current state of research, hotspots, evolution, and trends in the field. We discussed current research challenges and possible future research directions to help researchers identify appropriate research directions and conduct subsequent research more efficiently. Originality/value Compared with previous related studies, this study is innovative as we provide a comprehensive and specific analysis of the literature in the field over the last 20 years to help readers gain a comprehensive understanding of the current state of research, hotspots, evolution, and trends in the field and discuss current research challenges and possible future research directions to help researchers identify appropriate research directions and conduct subsequent research more efficiently.

Journal of Data and Information Science
Max Planck Institute for Solid State Research (DE), Eastern University (BD)
Partnerships for the goals
Openalex Percentile: Top 10%
Geophysical and Geoelectrical Methods
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