Connection and stratification in research collaboration: an analysis of the COLLNET network
Information Processing and Management: an International Journal - Special issue: Informetrics
Analyzing (social media) networks with NodeXL
Proceedings of the fourth international conference on Communities and technologies
Applying centrality measures to impact analysis: A coauthorship network analysis
Journal of the American Society for Information Science and Technology
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
The structure of collaboration in the Journal of Finance
Scientometrics
Annual Review of Information Science and Technology
The cognitive structure of Library and Information Science: Analysis of article title words
Journal of the American Society for Information Science and Technology
Collaboration structures in Slovenian scientific communities
Scientometrics
Trend and efficiency analysis of co-authorship network
Scientometrics
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With the world in the midst of an energy crisis, recent research has placed considerable emphasis on harnessing renewable and sustainable energy while efficiently using fossil fuels. Researchers create and sustain academic societies as a result of social interactions. This study takes a social network perspective to understand researchers' associations using two Organisation of Islamic Co-operation nations, Turkey and Malaysia, in the fast-developing field of `Energy Fuels'. The study found both similarities and differences in the scholarly networks of these two countries. The mean distance between the authors in the Turkey and Malaysia networks was 8.4 and 6.5, respectively, confirming the small world nature of these networks. The popularity, position, and prestige of the authors in the network, as determined through centrality measures, had a statistically significant effect on research performance. These measures, however, were far more correlated with the research performance of the authors in the Malaysia network than in the Turkey network. PageRank centrality was found to be the most efficient topological measure when it came to correlation with research performance. We used authors' `degree' to reach to the `core' (`Deg-Core') of the network (in contrast to the K-Core method), which was found to capture more productive authors. A method to detect academic communities of productive authors by extracting motifs (large cliques) from the network is suggested. Finally, we visualize the cognitive structure of both countries using a 2-mode network representing research focus areas (RFAs) and prominent authors working in these RFAs.