Abstract
BackgroundThe analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly.Methodology/Principal FindingsMeasures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality), we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count) and formation (tie strength between authors) of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of ‘steel structure’ for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s) in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s). Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations.Conclusions/SignificanceAuthors’ network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.
Highlights
Study of co-authorship network has been the subject of intense interest in recent years because this type of network depicts academic society and represents the structure of our knowledge in an open innovation community [1,2,3]
For our complete research dataset, it is revealed that the average of the degree centrality and betweenness centrality values of all co-authors of a scientific publication have positive correlations with the citation count of that paper
For National University of Singapore (NUS) and Monash University research group, we notice that the average of the degree centrality values of all co-authors of a scientific publication has a positive correlation with the citation count of that publication
Summary
Study of co-authorship network has been the subject of intense interest in recent years because this type of network depicts academic society and represents the structure of our knowledge in an open innovation community [1,2,3]. Researchers have been analyzing co-authorship network extensively to explore factors affecting behaviour, performance and motivation of scientific collaborations [5,6,7]. Somewhat similar to the much studied citation networks, coauthorship implies a much stronger bond among authors than citation. Unlike citation networks where nodes are papers and the links between them are citations [8], in a co-authorship network nodes represent authors and links between nodes imply a scientific collaboration. The analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. Little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly
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