Result: Comparative study on structure and correlation among author co-occurrence networks in bibliometrics

Title:
Comparative study on structure and correlation among author co-occurrence networks in bibliometrics
Source:
Selected Papers of the 14th International Conference of the International Society for Scientometrics and Informetrics (ISSI), July 15-19, 2013, Vienna, AustriaScientometrics (Print). 101(2):1345-1360
Publisher Information:
Dordrecht: Springer, 2014.
Publication Year:
2014
Physical Description:
print, 2 p.1/4
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Information Management, Wuhan University, Wuhan, China
ISSN:
0138-9130
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation

FRANCIS
Accession Number:
edscal.28892108
Database:
PASCAL Archive

Further Information

This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.