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Network effects on scientific collaborations.

Uddin S, Hossain L, Rasmussen K - PLoS ONE (2013)

Bottom Line: However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly.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.Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.

View Article: PubMed Central - PubMed

Affiliation: Project Management Program and Centre for Complex Systems Research, The University of Sydney, Sydney, Australia. shahadat.uddin@sydney.edu.au

ABSTRACT

Background: The 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 findings: Measures 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/significance: Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.

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Related in: MedlinePlus

Network attributes for each author and the tie strength of that author with all her/his co-authors.Three basic centrality measures (i.e., degree centrality, closeness centrality and betweenness centrality) are considered. CRD stands for ‘Complete Research Dataset’.
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pone-0057546-g005: Network attributes for each author and the tie strength of that author with all her/his co-authors.Three basic centrality measures (i.e., degree centrality, closeness centrality and betweenness centrality) are considered. CRD stands for ‘Complete Research Dataset’.

Mentions: We then plot the tie strength between two co-authors against the network attributes of each of the co-authors in Figure 5. This figure illustrates the research dataset in terms of network position of each author and the tie strength with all her/his co-author(s). We considered degree centrality, closeness centrality and betweenness centrality to measure network position of each author. From this figure, it is evident that there is a significant difference in network measures for two co-authors who either form a strong tie or weak tie. This could be explained by a student-supervisor relation where the student, who does not collaborate with any other author, publish many paper (i.e., strong tie strength) or very few paper (i.e., low tie strength) with the supervisor who is highly connected and well cited. Some of the authors do not play any bridging role in the co-authorship network as reflected in the betweenness centrality values (some of these values are zero).


Network effects on scientific collaborations.

Uddin S, Hossain L, Rasmussen K - PLoS ONE (2013)

Network attributes for each author and the tie strength of that author with all her/his co-authors.Three basic centrality measures (i.e., degree centrality, closeness centrality and betweenness centrality) are considered. CRD stands for ‘Complete Research Dataset’.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585377&req=5

pone-0057546-g005: Network attributes for each author and the tie strength of that author with all her/his co-authors.Three basic centrality measures (i.e., degree centrality, closeness centrality and betweenness centrality) are considered. CRD stands for ‘Complete Research Dataset’.
Mentions: We then plot the tie strength between two co-authors against the network attributes of each of the co-authors in Figure 5. This figure illustrates the research dataset in terms of network position of each author and the tie strength with all her/his co-author(s). We considered degree centrality, closeness centrality and betweenness centrality to measure network position of each author. From this figure, it is evident that there is a significant difference in network measures for two co-authors who either form a strong tie or weak tie. This could be explained by a student-supervisor relation where the student, who does not collaborate with any other author, publish many paper (i.e., strong tie strength) or very few paper (i.e., low tie strength) with the supervisor who is highly connected and well cited. Some of the authors do not play any bridging role in the co-authorship network as reflected in the betweenness centrality values (some of these values are zero).

Bottom Line: However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly.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.Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.

View Article: PubMed Central - PubMed

Affiliation: Project Management Program and Centre for Complex Systems Research, The University of Sydney, Sydney, Australia. shahadat.uddin@sydney.edu.au

ABSTRACT

Background: The 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 findings: Measures 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/significance: Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations.

Show MeSH
Related in: MedlinePlus