May 23, 2022 | News | Interview

How to Use Bibliometric Data for Demographic Research

© MPIDR/Wilhelm

Bibliometric data, information extracted from scientific publications, can be considered as a source of digital trace data. In this interview, MPIDR Researcher Aliakbar Akbaritabar explains how re-purposing bibliometric data allows answering social science and demographic questions.

Dr. Akbaritabar, what are bibliometric data?

Bibliometric data are information that is extracted from scientific publications. That includes, for example, authors’ names, academic affiliation addresses, reference lists, publication year and also textual data like title, abstract, manuscript’s full text and keywords.

There are diverse scientific fields like science of science, scientometrics or sociology of science that use bibliometric data. What types of research questions can be explored with it?

Questions to ask are, for example: How scientists do science? Who collaborates with whom? What kind of teams develop and produce more scientific breakthroughs? In these cases, bibliometric data is used to trace scientists’ behavior. Research questions can also be broader to investigate academia and the science system in general, for instance gender disparities. In addition, some research questions focus on the content of scientific publications to summarize or systematically review them. They aim to see how specific fields are developing or specific topics are being studied.

That sounds like a lot of possibilities…

Yes, absolutely. I have to say that these are only a few examples of how bibliometric data is used to study the science system and scientists’ behavior or the content of scientific publications. These are all broad fields with very specialized research questions.

How can bibliometric data be leveraged for demographic research?

The usage in demographic research can roughly be divided into two groups. One group looks at the population of scholars and uses bibliometric data to study the composition of different national science systems, and their development over time. This application is similar to the research question on gender disparities, I mentioned above. Another group of studies re-purposes bibliometric data and treats it similar to digital traces to study, for example, scholars’ mobility and migration. These studies investigate academic affiliation addresses and use them as proxy for academic’s residential addresses. Simply put, changes in these addresses could signal a mobility event, which helps us studying scientific and scholarly migration worldwide.

Researchers at the MPIDR are working with bibliometric data for quite a while now, what are your current findings?

Before I joined the MPIDR in 2021, colleagues had already developed interesting research projects in the broader area of computational social science. As a computational social scientist with a background in sociology, I relied on their work to advance the research area a bit further. I investigated sub-national regions inside countries and scholarly migration within countries in contrast to international migration, for instance.

What is next in line?

We are extremely excited that the use of bibliometric data for demographic research has attracted attention from the demographic community. We presented our findings at prominent demographic conferences like PAA, EPC, IUSSP/IPC. As a pre-conference event at the upcoming EPC 2022 in Groningen we are going to organize a workshop with a panel discussion that is hosted by the IUSSP Panel on Digital Demography

EPC 2022 Preconference Workshop

IUSSP Panel on Digital Demography: Using bibliometric data in demographic research

About

Aliakbar Akbaritabar is a computational social scientist. He is currently working on topics related (but not limited) to science of science, scholarly migration, social networks, collaboration networks, and of course computational social science. He is looking forward to collaborate on research ideas close to these themes, using computational tools and techniques to answer social scientific questions. Ali on Twitter: @akbaritabar

References

Kashyap, R., Rinderknecht, R. G., Akbaritabar, A., Alburez-Gutierrez, D., Gil-Clavel, S., Grow, A., Kim, J., Leasure, D. R., Lohmann, S., Negraia, D. V., Perrotta, D., Rampazzo, F., Tsai, C.-J., Verhagen, M. D., Zagheni, E., & Zhao, X. (2022). Digital and Computational Demography. SocArXiv. 10.31235/osf.io/7bvpt

Piolatto, M., Bianchi, F., Rota, M., Marengoni, A., Akbaritabar, A., Squazzoni, F.: The effect of social relationships on cognitive decline in older adults: An updated systematic review and meta-analysis of longitudinal cohort studies. BMC Public Health (2022). DOI: 10.1186/s12889-022-12567-5

Akbaritabar, A., Stephen, D., Squazzoni, F: A study of referencing changes in preprint-publication pairs across multiple fields. Journal of Informetrics (2022). DOI 10.1016/j.joi.2022.101258

Akbaritabar, A., Zagheni, E., & Zhao, X.: Internal versus international scholarly mobility and migration worldwide. International Population Conference (IPC2021), International Union for the Scientific Study of Population (IUSSP) (2021). DOI: https://ipc2021.popconf.org/abstracts/211016

Akbaritabar, A., Squazzoni, F.: Gender Patterns of Publication in Top Sociological Journals. Science, Technology, & Human Values. (2020). DOI: 10.1177/0162243920941588

Aref, S., Zagheni, E., West, J.: The Demography of the Peripatetic Researcher: Evidence on Highly Mobile Scholars from the Web of Science. In I. Weber, K. M. Darwish, C. Wagner, E. Zagheni, L. Nelson, S. Aref, & F. Flöck (Eds.), Social Informatics (pp. 50–65). Springer International Publishing. (2019). DOI: 10.1007/978-3-030-34971-4_4

Miranda-González, A., Aref, S., Theile, T., & Zagheni, E.: Scholarly migration within Mexico: Analyzing internal migration among researchers using Scopus longitudinal bibliometric data. EPJ Data Science (2020). DOI: 10.1140/epjds/s13688-020-00252-9

Subbotin, A., Aref, S.: Brain drain and brain gain in Russia: Analyzing international migration of researchers by discipline using Scopus bibliometric data 1996–2020. Scientometrics (2021). DOI: 10.1007/s11192-021-04091-x

Zhao, X., Aref, S., Zagheni, E., & Stecklov, G.: Return migration of German-affiliated researchers: Analyzing departure and return by gender, cohort, and discipline using Scopus bibliometric data 1996–2020. Scientometrics (2022). DOI: 10.1007/s11192-022-04351-4

Castro Torres, A. F., Alburez-Gutierrez, D.: North and South: Naming practices and the hidden dimension of global disparities in knowledge production. Proceedings of the National Academy of Sciences (2022).  DOI: 10.1073/pnas.2119373119