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      Scientific authorship and collaboration network analysis on malaria research in Benin: papers indexed in the web of science (1996–2016)

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          Abstract

          Background

          To sustain the critical progress made, prioritization and a multidisciplinary approach to malaria research remain important to the national malaria control program in Benin. To document the structure of the malaria collaborative research in Benin, we analyze authorship of the scientific documents published on malaria from Benin.

          Methods

          We collected bibliographic data from the Web Of Science on malaria research in Benin from January 1996 to December 2016. From the collected data, a mulitigraph co-authorship network with authors representing vertices was generated. An edge was drawn between two authors when they co-author a paper. We computed vertex degree, betweenness, closeness, and eigenvectors among others to identify prolific authors. We further assess the weak points and how information flow in the network. Finally, we perform a hierarchical clustering analysis, and Monte-Carlo simulations.

          Results

          Overall, 427 publications were included in this study. The generated network contained 1792 authors and 116,388 parallel edges which converted in a weighted graph of 1792 vertices and 95,787 edges. Our results suggested that prolific authors with higher degrees tend to collaborate more. The hierarchical clustering revealed 23 clusters, seven of which form a giant component containing 94% of all the vertices in the network. This giant component has all the characteristics of a small-world network with a small shortest path distance between pairs of three, a diameter of 10 and a high clustering coefficient of 0.964. However, Monte-Carlo simulations suggested our observed network is an unusual type of small-world network. Sixteen vertices were identified as weak articulation points within the network.

          Conclusion

          The malaria research collaboration network in Benin is a complex network that seems to display the characteristics of a small-world network. This research reveals the presence of closed research groups where collaborative research likely happens only between members. Interdisciplinary collaboration tends to occur at higher levels between prolific researchers. Continuously supporting, stabilizing the identified key brokers and most productive authors in the Malaria research collaborative network is an urgent need in Benin. It will foster the malaria research network and ensure the promotion of junior scientists in the field.

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          Most cited references21

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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                Author and article information

                Contributors
                roseric_2000@yahoo.fr
                zjharper@uwm.edu
                rofargossa@yahoo.fr
                welzig@mcw.edu
                mcroy@uwm.edu
                Journal
                Glob Health Res Policy
                Glob Health Res Policy
                Global Health Research and Policy
                BioMed Central (London )
                2397-0642
                6 April 2018
                6 April 2018
                2018
                : 3
                : 11
                Affiliations
                [1 ]GRID grid.473220.0, Centre de Recherche Entomologique de Cotonou, ; Cotonou, Benin
                [2 ]ISNI 0000 0001 0695 7223, GRID grid.267468.9, University of Wisconsin Milwaukee, ; Milwaukee, WI 53211 USA
                [3 ]ISNI 0000 0001 2111 8460, GRID grid.30760.32, Medical College of Wisconsin, ; Milwaukee, WI 53226 USA
                Article
                67
                10.1186/s41256-018-0067-x
                5887226
                29637087
                9039a998-f9d3-47a2-88d0-606ab1a3712a
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 July 2017
                : 12 March 2018
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                network analysis,scientific collaboration,co-authorship,malaria,benin

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