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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

Illustration of a co-authorship network.(a) author-paper network for three papers written by four authors; (b) corresponding co-authorship network; and (c) co-authorship network showing same network attributes for each author. Au stands for Author, P stands for Paper and At stands for network attribute (e.g., degree centrality) of authors. Although in this figure we consider two attributes (i.e., At1 and At2) for illustration, we consider network attributes of degree centrality, closeness centrality and betweenness centrality of all authors for research analysis in this study.
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pone-0057546-g001: Illustration of a co-authorship network.(a) author-paper network for three papers written by four authors; (b) corresponding co-authorship network; and (c) co-authorship network showing same network attributes for each author. Au stands for Author, P stands for Paper and At stands for network attribute (e.g., degree centrality) of authors. Although in this figure we consider two attributes (i.e., At1 and At2) for illustration, we consider network attributes of degree centrality, closeness centrality and betweenness centrality of all authors for research analysis in this study.

Mentions: Figure 1 and Figure 2 conceptualize our research questions with illustration. Figure 1A shows author-paper network for three papers (i.e., P1, P2 and P3) that are written by four authors (i.e., Au1, Au2, Au3 and Au4). The corresponding co-authorship network of Figure 1A is illustrated in Figure 1B. In Figure 1C, we exhibit, in addition to co-authorship network, the network measures/attributes (i.e., At1 and At2) of each co-author. These network measures for each co-author are measured from Figure 1B. We consider only two network measures for illustration. There could be more network measures for authors to be considered that depend mainly on the research question(s) under consideration. Figure 2A shows the illustration of our first research question (i.e., how is the citation count of a research paper influenced by the network measures of its co-author(s)?). Our second research question (i.e., how is the strength of scientific relations between two authors influenced by their network positions in a co-authorship network?) is illustrated in Figure 2B. These illustrations of our research questions (i.e., Figure 2A and Figure 2B) are based on Figure 1C. The summary of our research investigation is illustrated in Figure 2C.


Network effects on scientific collaborations.

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

Illustration of a co-authorship network.(a) author-paper network for three papers written by four authors; (b) corresponding co-authorship network; and (c) co-authorship network showing same network attributes for each author. Au stands for Author, P stands for Paper and At stands for network attribute (e.g., degree centrality) of authors. Although in this figure we consider two attributes (i.e., At1 and At2) for illustration, we consider network attributes of degree centrality, closeness centrality and betweenness centrality of all authors for research analysis in this study.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0057546-g001: Illustration of a co-authorship network.(a) author-paper network for three papers written by four authors; (b) corresponding co-authorship network; and (c) co-authorship network showing same network attributes for each author. Au stands for Author, P stands for Paper and At stands for network attribute (e.g., degree centrality) of authors. Although in this figure we consider two attributes (i.e., At1 and At2) for illustration, we consider network attributes of degree centrality, closeness centrality and betweenness centrality of all authors for research analysis in this study.
Mentions: Figure 1 and Figure 2 conceptualize our research questions with illustration. Figure 1A shows author-paper network for three papers (i.e., P1, P2 and P3) that are written by four authors (i.e., Au1, Au2, Au3 and Au4). The corresponding co-authorship network of Figure 1A is illustrated in Figure 1B. In Figure 1C, we exhibit, in addition to co-authorship network, the network measures/attributes (i.e., At1 and At2) of each co-author. These network measures for each co-author are measured from Figure 1B. We consider only two network measures for illustration. There could be more network measures for authors to be considered that depend mainly on the research question(s) under consideration. Figure 2A shows the illustration of our first research question (i.e., how is the citation count of a research paper influenced by the network measures of its co-author(s)?). Our second research question (i.e., how is the strength of scientific relations between two authors influenced by their network positions in a co-authorship network?) is illustrated in Figure 2B. These illustrations of our research questions (i.e., Figure 2A and Figure 2B) are based on Figure 1C. The summary of our research investigation is illustrated in Figure 2C.

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