• Analyzing evolution of researc...

Result: Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks

Title:
Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks
Authors:
XIAOGUANG WANG, QIKAI CHENG, WEI LU
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):1253-1271
Publisher Information:
Dordrecht: Springer, 2014.
Publication Year:
2014
Physical Description:
print, 2 p
Original Material:
INIST-CNRS
Subject Terms:
Information and communication sciences, Sciences de l'information communication, Documentation, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Sciences de l'information. Documentation, Information science. Documentation, Sciences de l'information et des bibliothèques. Etude d'ensemble, Library and information science. General aspects, Bibliométrie. Scientométrie. Evaluation, Bibliometrics. Scientometrics. Evaluation, Sciences de l'information et de la communication, Information and communication sciences, Bibliométrie. Scientométrie, Bibliometrics. Scientometrics, Algorithme, Algorithm, Algoritmo, Analyse cooccurrence, Cooccurrence analysis, Análisis coocurrencia, Analyse mots associés, Coword analysis, Análisis palabras asociadas, Recherche scientifique, Scientific research, Investigación científica, Mot associé, Coword, Co-word analysis, Emerging trend detection, Network communities, Science mapping, Topic evolution
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Center for Information Resources Research, Wuhan University, Wuhan, China
School of Information Management, Wuhan University, Wuhan, China
ISSN:
0138-9130
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28892103
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.28892103
Database:
PASCAL Archive

Further Information

Understanding the evolution of research topics is crucial to detect emerging trends in science. This paper proposes a new approach and a framework to discover the evolution of topics based on dynamic co-word networks and communities within them. The NEViewer software was developed according to this approach and framework, as compared to the existing studies and science mapping software tools, our work is innovative in three aspects: (a) the design of a longitudinal framework based on the dynamics of co-word communities; (b) it proposes a community labelling algorithm and community evolution verification algorithms; (c) and visualizes the evolution of topics at the macro and micro level respectively using alluvial diagrams and coloring networks. A case study in computer science and a careful assessment was implemented and demonstrating that the new method and the software NEViewer is feasible and effective.