Co‐Authorship Network Analysis in Industrial Ecology Research Community
Bibliographic Data
| ID | 19467249 |
|---|---|
| Authors | Junbeum Kim (0000-0003-0665-7989, Université de Technologie de Troyes, corresponding author), Charles Pérez (0000-0001-9030-5331, Paris School of Business) |
| Year | 2015 |
| Volume | 19 |
| Issue | 2 |
| Pages | 222-235 |
| Publication date | 2015-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Industrial Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1088-1980 • E-ISSN: 1530-9290 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1111/jiec.12256 |
| OpenAlex | W1561068712 |
| Language | EN |
| Citations received | 2 |
| References cited | 26 |
Many scientific collaboration networks have been extensively studied from different perspectives, such as network degree analysis or centrality. However, there has been little study of the scientific collaboration network in the industrial ecology (IE) research domain and community. In this study therefore, we collected co‐authorship keywords and related data from 1,032 publications between 1997 and 2012 from the most influential journal on the topic: the Journal of Industrial Ecology . An evaluation of publications in terms of network characteristics was conducted. Journal characteristics, such as publications by each author, number of co‐authors per paper, and keywords, were identified. Further, we developed a co‐authorship network and maps with network centrality analysis, components, and cluster analysis. The results of this study clearly show the main topics of the science, structure of scientific collaboration, and status of individual researchers within the IE research community
Biology · Centrality · Complex network · Data science · Industrial ecology · Network analysis · Network science · Social network analysis · Social science · Sociology · Sustainability · World Wide Web · Complex Network Analysis Techniques · Computer Science · Engineering · scientometrics and bibliometrics research · Sustainable Industrial Ecology · Ecology
Citation indexing, its theory and application in science, technology, and humanities
Fast algorithm for detecting community structure in networks
Scientific collaboration networks. I. Network construction and fundamental results
Analysis and Visualization of Social Networks
Scale-Free Networks
Classes of small-world networks
Coauthorship networks and patterns of scientific collaboration
Understanding the Evolution of Industrial Symbiosis Research
Centrality in social networks conceptual clarification
Some analyses of Erdős collaboration graph
The Impact of Research Collaboration on Scientific Productivity
A Set of Measures of Centrality Based on Betweenness
The Structure of a Social Science Collaboration Network
| Citations per year | 0.18 |
|---|---|
| Citation span | 2015 - 2024 (10) |
| Highly cited | No |