A new approach for detecting scientific specialties from raw cocitation networks

Matthew L. Wallace, Yves Gingras and Russell Duhon

Journal of the American Society for Information Science and Technology, 2009, vol. 60, issue 2, 240-246

Abstract: We use a technique recently developed by V. Blondel, J.‐L. Guillaume, R. Lambiotte, and E. Lefebvre (2008) to detect scientific specialties from author cocitation networks. This algorithm has distinct advantages over most previous methods used to obtain cocitation “clusters” since it avoids the use of similarity measures, relies entirely on the topology of the weighted network, and can be applied to relatively large networks. Most importantly, it requires no subjective interpretation of the cocitation data or of the communities found. Using two examples, we show that the resulting specialties are the smallest coherent “groups” of researchers (within a hierarchy of cluster sizes) and can thus be identified unambiguously. Furthermore, we confirm that these communities are indeed representative of what we know about the structure of a given scientific discipline and that as specialties, they can be accurately characterized by a few keywords (from the publication titles). We argue that this robust and efficient algorithm is particularly well‐suited to cocitation networks and that the results generated can be of great use to researchers studying various facets of the structure and evolution of science.

Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
https://doi.org/10.1002/asi.20987

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:60:y:2009:i:2:p:240-246

Ordering information: This journal article can be ordered from
https://doi.org/10.1002/(ISSN)1532-2890

Access Statistics for this article

More articles in Journal of the American Society for Information Science and Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().