Christian Boulanger, Naomi Creutzfeldt and Jen Hendry
This post marks the first in a series of three blog posts that accompany our paper “The Journal of Law and Society in Context: A Bibliometric Analysis”, published in the Journal of Law and Society (vol. 51, issue 1, 2024). In these posts, we expand on the methodological aspects of our analysis to share visualisations that could not be included in the published article.
In each of the posts, we will explore three different types of analysis:
- Descriptive analyses of bibliographic metadata
- Text-linguistic analyses of content (metadata or full text), and
- Network analyses of citation graphs computed from existing and self-generated data.
What are bibliometrics?
Bibliometrics have been defined as “the application of mathematics and statistical methods to books and other media of communication”. As this 1969 definition shows, it began as the statistical study of books. As the primary medium of scholarly communication shifted from books to articles, the primary focus of bibliometrics shifted as well, increasingly becoming the study of citation data. Bibliometrics overlaps with but is usually distinguished from the fields of scientometrics and informetrics, which refer to the study of scientific production beyond the study of publications. These fields of research tend to deal with large quantities of metadata, and not usually so much with the content of academic publishing. Their theories and methods are most often used in the domain of library and information science, and also in the measurement and evaluation of the productivity and the impact of scholars, research fields or academic organizations. Our approach is somewhat different. We are not bibliometricians: our interest in the use of these methods is to tease out the history of socio-legal ideas, the agency of scholars, and the role of institutions, all in a qualitative sense. To this end, we combine the aforementioned types of analysis to get an initial, although necessarily incomplete, picture of socio-legal studies as it appears in the JLS data.
Descriptive Analyses of Bibliographic Metadata
The most straightforward form of bibliometric analysis is the presentation of metrics derived from bibliographic metadata. This data is easy to retrieve at no cost. For example, for retrieving metadata on journal articles, you can use the online API (Application Programming Interface) at https://api.crossref.org. Book metadata is a bit more complicated to get, but various national libraries offer access to their holdings via an API. For example, the British National Bibliography contains books and journals published in the UK or Republic of Ireland since 1950.
Metadata allows to run basic analyses that is indicative of broad trends. For example, using the data from crossref.org, we can elucidate a steady growth in the number of articles published in the JLS per year (Fig. 1).
When isolating publication data to the JLS specifically, it is possible to identify the authors who most frequently publish in the Journal (fig 2).
Of course, there is likely to be an over-representation of past and present editorial board members within this dataset due to the frequency with which the board initiates and publishes special issues. Nevertheless, this reveals interesting trends regarding the authors that have a close relationship with the Journal and the roles they have played in shaping the field of socio-legal studies. Finally, descriptive analysis was used to chart the frequency of sole and co-authored publications in the JLS (Fig. 3).
Other metadata analyses focus on the keywords or abstracts of articles, and the changes in their use that can be detected over time, with a view to detecting emerging topics within different (social) scientific fields (for example, Zhang et al. 2017). The problem with keywords, however, is that they are used inconsistently, even within the same disciplines – and in this regard socio-legal studies is no different: there is no commonly accepted conceptual taxonomy or shared vocabulary for socio-legal topics that can be used to assign keywords to articles.
To ensure accountability and transparency, the figures, codes and data from our study are publicly available in an open-access GitHub repository.
This type of analysis is still in its infancy, and we do not claim completeness; these contributions need to be understood as preliminary. Our aim is to provides the start of a conversation, rather than results set in stone. We expect and welcome critical feedback from both traditions: qualitative-hermeneutical history of ideas scholars as well as those who use quantitative methods from bibliometrics to pursue questions in the history of science.
We encourage readers to engage with findings that have emerged across our three analyses: the next post in this series focuses on text-linguistic analyses of content.