Betweenness centrality as an indicator of the interdisciplinarity of scientific journals

By Loet Leydesdorff. J. Assoc. Inf. Sci. Technol., 2007

609 citations recorded by the source corpus.

In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation Reports of the Science Citation Index and the Social Sciences Citation Index 2004 (Thomson ISI, Philadelphia, PA), and then also in relation to local citation environments that can be considered as proxies of specialties and disciplines. Betweenness centrality is shown to be an indicator of the interdisciplinarity of journals, but only in local citation environments and after normalization; otherwise, the influence of degree centrality (size) overshadows the betweenness-centrality measure. The indicator is applied to a variety of citation environments, including policy-relevant ones like biotechnology and nanotechnology. The values of the indicator remain sensitive to the delineations of the set because of the indicator's local character. Maps showing interdisciplinarity of journals in terms of betweenness centrality can be drawn using information about journal citation environments, which is available online.

Subfields: Information Systems, Statistical and Nonlinear Physics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2d67aa01b35412077c1450726b09166d7c5c98f6

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Citations in the corpus

How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management (2012, background): “fter submission of this article, Leydesdorff and Rafols (2012) developed”
A Principal Component Analysis of 39 Scientific Impact Measures (2009, background): “Using another social network measure, Leydesdorﬀ (2007) [18] proposes betweenness centrality as an indicator of a journal’s interdisciplinary power.”
Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience (2009, methodology): “e measures can be interpreted in terms of network centralities, which were introduced in bibliometrics to study research communities (Otte and Rousseau, 2002) and interdisciplinarity in journal sets (Leydesdorff, 2007). Mean linkage strength S is the mean degree centrality normalised by network size”
The science of science: from the perspective of complex systems (2017, positive): “Similar to the keyword networks, the betweenness centrality in this network was shown to be an indicator of the interdisciplinarity of journals [100].”
Bibliometrics to webometrics (2008, background): “Moreover, citation analysis in conjunction with visualization also helps to understand the structure of individual fields, and is particularly useful for emerging and rapidly developing important research areas, such as nanotechnology and biotechnology [42].”
Measuring Scholarly Impact (2014, background): “For example, Leydesdorff explored the usefulness of betweenness centrality to measure the interdisciplinarity of journals (Leydesdorff, 2007; Leydesdorff & Rafols, 2011).”
International collaboration in science and the formation of a core group (2008, background): “We assume that authors listing two addresses have colleagues in both institutions and therefore fall within a broad definition of collaboration. spurious when based on multilateral co-occurrences at the document level (Waltman & Van Eck, 2007; Leydesdorff, 2007a).”
Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus (2015, neutral): “ Besides this, Katz and Hicks (1995), Leydesdorff (2007), and Leydesdorff and Rafols (2009) have indicated that the WoS classification system is based on a comprehensive consideration of citation patterns, titles of journals, and expert opinion.”