Detecting research fronts using different types of weighted citation networks

• Published in: Journal of engineering and technology management Vol. 32; pp. 129 - 146
• Main Authors: Fujita, Katsuhide, Kajikawa, Yuya, Mori, Junichiro, Sakata, Ichiro
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.2014; Elsevier Sequoia S.A
• Subjects: Analogies; Bibliographic coupling; Bibliometrics; Citation analysis; Citation network analysis; Citations; Clusters; Comparative analysis; Decision support; Innovations; Joining; Management; Nanostructure; Networks; Performance evaluation; Research front; Studies; Citation network analysis; O3; Bibliometrics; Research front; Decision support
• ISSN: 0923-4748; 1879-1719
• DOI: 10.1016/j.jengtecman.2013.07.002

In this paper, we investigate the performance of different types of weighted citation networks for detecting emerging research fronts by a comparative study. Three citation patterns including direct citation, co-citation and bibliographic coupling, have been tested in three research domains including gallium nitride, complex networks, and nano-carbon. These three patterns of citation networks are constructed for each research domain, and the papers in those domains are divided into clusters to detect the research front. Additionally, we apply some measures to weighted citations like difference in publication years between citing and cited papers and similarities of keywords between them, which are expected to be able to effectively to detect emerging research fronts. To investigate the performance of different types of weighted citation networks for detecting emerging research fields, we evaluate the performance of each approach by using the following measures of extracted research fronts: visibility, speed, and topological and textual relevance.