A bibliometric approach to finding fields that co-evolved with information technology
Shino Iwami (),
Arto Ojala,
Chihiro Watanabe and
Pekka Neittaanmäki
Additional contact information
Shino Iwami: Osaka University
Arto Ojala: University of Jyväskylä
Chihiro Watanabe: University of Jyväskylä
Pekka Neittaanmäki: University of Jyväskylä
Scientometrics, 2020, vol. 122, issue 1, No 2, 3-21
Abstract:
Abstract Among the declining industries, for example music industry, some have been revived by information technology (IT). At the same time, in academic fields, some have expected co-evolutions between IT and other fields to cause the resurgence of either field. In this research, the clustering of citation networks with 14,438 academic papers resulted in the identification of 28 academic fields in the areas “Computer Science” or “Information Science and Library Science.” Co-evolutions between these 28 fields and citing fields to the 28 fields were evaluated by an investigation of contents; a methodology to search co-evolutions was also proposed. This paper proposes that pairs of academic fields (with both high correlation and high dissimilarity) co-evolve, and some co-evolving pairs of academic fields were found. This research contributes to the discovery of the co-evolution between academic fields.
Keywords: Co-evolution; Academic landscape; Big data; Network analysis; Citation analysis; Clustering; Unsupervised classification; Cosine similarity; Horizon scanning; Exploratory scanning (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-019-03284-9 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:122:y:2020:i:1:d:10.1007_s11192-019-03284-9
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-019-03284-9
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 ().