Software for Bibliometrics Analysis and Visualization

Bibliometric Analysis

& 

Visualization Tools

        Bibliometrics is the statistical analysis of books, articles, and other publications. This approach measures the productivity and impact of authors or researchers, offering insights into their contributions to a field. It also plays a crucial role in determining journal impact factors, which assess the influence and quality of academic journals. Furthermore, bibliometric data can be visualized to explore and comprehend the relationships between publications, providing a clearer understanding of scholarly communication and research trends.

Bibliometric analysis techniques are broadly classified into two categories:

    1. Performance analysis evaluates the contributions of various research entities, such as authors, institutions, or countries.

    2. Science mapping examines the relationships and connections between these research entities, providing insights into collaboration patterns and thematic developments.

 

Bibliometrics Analysis and Visualization Tools

This blog post will examine various bibliometric analysis tools that can enhance your research and provide valuable insights.

1.BibExcel (homepage.univie.ac.at/juan.gorraiz/bibexcel/)

BibExcel is designed to assist a user in analyzing bibliographic data or any data of a textual nature formatted similarly. The idea is to generate data files that can be imported to Excel or any program that takes tabbed data records for further processing. Developed at Umeå University in Sweden, BibExcel is a flexible bibliometric processing tool designed to prepare data for analysis. Although it lacks visualization features, BibExcel enables users to process bibliographic data from prominent sources such as Web of Science and Scopus. It supports various analyses, including citation counts, co-authorship patterns, and bibliographic coupling.

2.  Bibliometrix (R Package)

This free and open-source software for data science, scientific research, and technical communication is an integrated development environment (IDE) for R.  Given its integration with R, Bibliometrix allows for high flexibility and reproducibility in data analysis, making it ideal for researchers who need in-depth control over data processing and statistical analyses.

3.  Biblioshiny (https://www.bibliometrix.org/home/index.php/layout/biblioshiny)

Biblioshiny is a web-based graphical interface designed for Bibliometrix, which is aimed at making bibliometric analysis accessible to users without programming expertise. With its intuitive interface, Biblioshiny allows researchers to perform analyses like collaboration networks and thematic evolution without requiring coding knowledge. It is particularly well-suited for exploratory data analysis and initial bibliometric studies. It works under the R Studio package.

4.  HistCite

HistCite is a software package used for bibliometric analysis and information visualization. It was developed by Eugene Garfield. It was created to assist researchers in visualizing the historical progression of scientific fields by producing "historiographs," which are chronological maps depicting citation relationships among documents in a specific dataset. HistCite has been discontinued and is no longer officially supported by Clarivate

5. ScientoPy (https://www.scientopy.com/en/)

ScientoPy is an open-source Python-based scientometric analysis tool. ScientoPy's straightforward design and integration with Python libraries for data manipulation make it an accessible tool for Python users seeking to analyze bibliometric data with ease.

6.  Sci2 Tool (https://sci2.cns.iu.edu/user/index.php)

The Science of Science (Sci2) Tool is a modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical, and network analysis and visualization of scholarly datasets at the micro (individual), meso (local), and macro (global) levels. Sci2 is well-suited for multi-dimensional bibliometric studies and supports comprehensive analysis of large datasets.

7. PoP (Publish or Perish) (https://harzing.com/resources/publish-or-perish)

Publish or Perish is a software tool that collects and analyzes academic citations. It gathers raw citation data from various sources such as crossref and Google Scholar, processes the information, and provides a range of citation metrics, such as the total number of papers, overall citations, and the h-index. This is not well suited for the complex analysis of data.

8. VOSviewer (https://www.vosviewer.com/)

VOSviewer is a software tool for constructing and visualizing bibliometric networks. These networks may for instance include journals, researchers, or individual publications, and they can be constructed based on citation, bibliographic coupling, co-citation, or co-authorship relations. VOSviewer also offers text mining functionality that can be used to construct and visualize co-occurrence networks of important terms extracted from a body of scientific literature.

9. BiblioMagika (https://bibliomagika.com/)

biblioMagika® is an Excel-based tool designed for conducting bibliometric analysis, focusing on assessing publication productivity and evaluating scholarly impact. It offers a range of calculations including total publications (TP), contributing authors (NCA), cited publications (NCP), total citations (TC), average citations per publication (C/P), average citations per cited publication (C/CP), h-index, g-index, m-index, citations sum within the h-core, cumulative total publication, and more. This analysis can be performed across various parameters such as publication year, source titles, authors, affiliations, and countries.

10. Pajek

Pajek is a network analysis tool that is particularly effective for analyzing and visualizing large-scale bibliometric networks. Initially created for social network analysis, Pajek has been successfully applied in bibliometrics for tasks like citation analysis, co-authorship networks, and clustering. Its strength lies in its ability to manage large datasets efficiently, utilizing advanced algorithms to reveal network structures.

11. Gephi (https://gephi.org/)

Gephi is an open-source network exploration and manipulation software. Developed modules can import, visualize, spatialize, filter, manipulate, and export all types of networks. The visualization module uses a special 3D render engine to render real-time graphs.  Gephi allows researchers to dynamically explore complex networks, such as citation and co-authorship networks. It offers a high degree of customization, enabling users to modify layouts, colors, and clustering algorithms, making it an excellent tool for examining relationships within large bibliometric datasets.

 

References

Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An Open Source Software for Exploring and Manipulating Networks. Proceedings of the International AAAI Conference on Web and Social Media, 3(1), 361–362. https://doi.org/10.1609/icwsm.v3i1.13937

Aria, M., & Cuccurullo, C. (2017). bibliometrix : An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Van Eck, N. J., & Waltman, L. (2009). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3

Library Guides: Bibliometrics: Tools and Software. (n.d.). https://liu.cwp.libguides.com/c.php?g=225325&p=4966525

Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional De La Informacion, 29(1). https://doi.org/10.3145/epi.2020.ene.03