Journal maps, interactive overlays, and the measurement of interdisciplinarity on the basis of <scp>S</scp>copus data (1996–2012)

Leydesdorff, Loet; Anegón, Félix de Moya; Guerrero‐Bote, Vicente P.

doi:10.1002/asi.23243

Cited by 45 publications

(54 citation statements)

References 39 publications

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“…In this sense, classification systems are an indispensable tool to study the structure and dynamics of scientific fields (Boyack, Klavans, & Börner, 2005;Glanzel & Schubert, 2003;Leydesdorff, Carley, & Rafols, 2013;Leydesdorff, de Moya-Anegón, & Guerrero-Bote, 2014;Ruiz-Castillo & Waltman, 2015;Y. Zhu & Yan, 2015;Waltman & van Eck, 2012;Zitt, 2015).…”

Section: Introductionmentioning

confidence: 99%

A delineating procedure to retrieve relevant publication data in research areas: the case of nanocellulose

2016

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Advances concerning publication-level classification system have been demonstrated striking results by dealing properly with emergent, complex and interdisciplinary research areas, such as nanotechnology and nanocellulose. However, less attention has been paid to propose a delineating method to retrieve relevant research areas on specific subjects. This study aims at proposing a procedure to delineate research areas addressed in case nanocellulose. We investigate how a bibliometric analysis could provide interesting insights into research about this sustainable nanomaterial. The research topics clustered by a Publication-level Classification System were used. The procedure involves an iterative process, which includes developing and cleaning a set of core publication regarding the subject and an analysis of clusters they are associated with. Nanocellulose was selected as the subject of study, but the methodology may be applied to any other research area or topic. A discussion about each step of the procedure is provided. The proposed delineation procedure enables us to retrieve relevant publications from research areas involving nanocellulose. Seventeen research topics were mapped and associated with current research challenges on nanocellulose.

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Section: Introductionmentioning

confidence: 99%

A delineating procedure to retrieve relevant publication data in research areas: the case of nanocellulose

2016

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“…Leydesdorff, de Moya‐Anegón, and Guerrero‐Bote () generated local maps on the basis of Scopus data of 2008. Recently, a global map with the facility to overlay data from Scopus for the period 1996–2012 was made available for interactive usage at http://www.leydesdorff.net/scopus_ovl (Leydesdorff, de Moya‐Anegón, & Guerrero‐Bote, in press). In the latter study, we developed a system equivalent to the interactive overlay maps that were generated for JCR data from 2011 (Chen & Leydesdorff, ; Leydesdorff, Rafols, & Chen, ).…”

Section: Introductionmentioning

confidence: 99%

Aggregated journal–journal citation relations in scopus and web of science matched and compared in terms of networks, maps, and interactive overlays

Leydesdorff

Anegón

Nooy

2015

Asso for Info Science & Tech

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We compare the network of aggregated journal-journal citation relations provided by the Journal Citation Reports (JCR) 2012 of the Science Citation Index (SCI)and Social Sciences Citation Index (SSCI) with similar data based on Scopus 2012. First, global and overlay maps were developed for the 2 sets separately. Using fuzzy-string matching and ISSN numbers, we were able to match 10,524 journal names between the 2 sets: 96.4% of the 10,936 journals contained in JCR, or 51.2% of the 20,554 journals covered by Scopus. Network analysis was pursued on the set of journals shared between the 2 databases and the 2 sets of unique journals. Citations among the shared journals are more comprehensively covered in JCR than in Scopus, so the network in JCR is denser and more connected than in Scopus. The ranking of shared journals in terms of indegree (i.e., numbers of citing journals) or total citations is similar in both databases overall (Spearman rank correlation ρ > 0.97), but some individual journals rank very differently. Journals that are unique to Scopus seem to be less important-they are citing shared journals rather than being cited by them-but the humanities are covered better in Scopus than in JCR.

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“…A scientogram or map of science based on SJR journals and their subsequent subject assignment derived from applying VOS community detection clustering. Despite various differences in the data set, methodology and techniques used in our proposal, there is considerable resemblance between this scientogram and those of Moya-Anegón et al (2007) or Leydesdorff et al (2015a;2015b). Indeed, the scientogram shape, like a croissant, was evoked by Leydesdorff et al (2013), who asserted that "this croissant-like structure also accords with Klavans and Boyack's (2009) conclusion that a consensus has increasingly emerged regarding the shape of journal maps based on aggregated citations".…”

Section: Discussionmentioning

confidence: 92%

Visualization and analysis of SCImago Journal & Country Rank structure via journal clustering

Gómez-Núñez¹,

Vargas-Quesada²,

Chinchilla‐Rodríguez

et al. 2016

AJIM

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PurposeThe objective was to visualize the structure of SCImago Journal & Country Rank (SJR) coverage of the extensive citation network of Scopus journals, examining this bibliometric portal through an alternative approach, applying clustering and visualization techniques to a combination of citation-based links. MethodologyThree SJR journal-journal networks containing direct citation, co-citation and bibliographic coupling links are built. The three networks were then combined into a new one by summing up their values, which were later normalized through geo-normalization measure. Finally, the VOS clustering algorithm was executed and the journal clusters obtained were labeled using original SJR category tags and significant words from journal titles. FindingsThe resultant scientogram displays the SJR structure through a set of communities equivalent to SJR categories that represent the subject contents of the journals they cover. A higher level of aggregation by areas provides a broad view of the SJR structure, facilitating its analysis and visualization at the same time. ValueThis is the first study using Persson's combination of most popular citation-based links (direct citation, co-citation and bibliographic coupling) in order to develop a scientogram based on Scopus journals from SJR. The integration of the three measures along with performance of the VOS community detection algorithm gave a balanced set of clusters. The resulting scientogram is useful for assessing and validating previous classifications as well as for information retrieval and domain analysis.

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Journal maps, interactive overlays, and the measurement of interdisciplinarity on the basis of Scopus data (1996–2012)

Cited by 45 publications

References 39 publications

A delineating procedure to retrieve relevant publication data in research areas: the case of nanocellulose

A delineating procedure to retrieve relevant publication data in research areas: the case of nanocellulose

Aggregated journal–journal citation relations in scopus and web of science matched and compared in terms of networks, maps, and interactive overlays

Visualization and analysis of SCImago Journal & Country Rank structure via journal clustering

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