Mapping the cognitive structure of astrophysics by infomap clustering of the citation network and topic affinity analysis

Theresa Velden (), Shiyan Yan () and Carl Lagoze ()
Additional contact information
Theresa Velden: University of Michigan School of Information
Shiyan Yan: University of Michigan School of Information
Carl Lagoze: University of Michigan School of Information

Scientometrics, 2017, vol. 111, issue 2, No 23, 1033-1051

Abstract: Abstract In this paper we use the information theoretic Infomap algorithm (Rosvall and Bergstrom in Proc Natl Acad Sci 105(4):1118–1123, 2008) iteratively in order to cluster the direct citation network of the Astro Data Set (publications in 59 astrophysical journals between 2003 and 2010.) We obtain 22 clusters of documents from the giant component of the network that we interpret as constituting ‘topics’ in the field of astrophysics. Upon investigation of the content of the topics we find a grouping of topics by shared features of their ‘journal signature’, that is the journals that are most characteristic for a topic due to their popularity and distinctiveness. These groups of topics match sub disciplines within the field. We generate a cognitive map of the field using a topic affinity network that shows what topics are disproportionally well connected (by citations) to other topics. The topology of the topic affinity network highlights a high-level organization of the field by sub-discipline and observational distance of the research object from Earth.

Keywords: Science mapping; Topic extraction; Network clustering; Direct citation network; Infomap; Topic labeling (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-017-2299-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:scient:v:111:y:2017:i:2:d:10.1007_s11192-017-2299-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-017-2299-9

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().