TY - GEN
T1 - Analysis of co-authorship network and the correlation between academic performance and social network measures
AU - Xu, Qianwen
AU - Chang, Victor
N1 - Publisher Copyright:
Copyright © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
PY - 2020
Y1 - 2020
N2 - This project conducted link analysis and graph cluster analysis to analyze the co-authorship network of 166 researchers, mainly from three top universities in Shanghai, China. The publication data of researchers in the area of social science between 2014 and 2016 were collected from Scopus, and the g index was calculated as their performance indicator. For this project, the centrality measures, the efficiency of the egocentric network were calculated as well as authorities and hubs were identified in the link analysis. In addition, clustering algorithms based on betweenness centrality were used to conduct the graph cluster analysis. Finally, in order to identify productive researchers, this project employed the Spearman correlation test to analyze the correlation between a researcher's performance and social network measures. Results from this test indicate that except for closeness centrality and degree centrality, the correlation between g-index and betweenness centrality, eigenvector centrality and efficiency is significant.
AB - This project conducted link analysis and graph cluster analysis to analyze the co-authorship network of 166 researchers, mainly from three top universities in Shanghai, China. The publication data of researchers in the area of social science between 2014 and 2016 were collected from Scopus, and the g index was calculated as their performance indicator. For this project, the centrality measures, the efficiency of the egocentric network were calculated as well as authorities and hubs were identified in the link analysis. In addition, clustering algorithms based on betweenness centrality were used to conduct the graph cluster analysis. Finally, in order to identify productive researchers, this project employed the Spearman correlation test to analyze the correlation between a researcher's performance and social network measures. Results from this test indicate that except for closeness centrality and degree centrality, the correlation between g-index and betweenness centrality, eigenvector centrality and efficiency is significant.
KW - Academic Performance
KW - Co-authorship Network
KW - Social Network Analysis
KW - Spearman Correlation Test
UR - http://www.scopus.com/inward/record.url?scp=85089515997&partnerID=8YFLogxK
U2 - 10.5220/0009428503590366
DO - 10.5220/0009428503590366
M3 - Conference Proceeding
AN - SCOPUS:85089515997
T3 - IoTBDS 2020 - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security
SP - 359
EP - 366
BT - IoTBDS 2020 - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security
A2 - Wills, Gary
A2 - Kacsuk, Peter
A2 - Chang, Victor
PB - SciTePress
T2 - 5th International Conference on Internet of Things, Big Data and Security, IoTBDS 2020
Y2 - 7 May 2020 through 9 May 2020
ER -