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Influence of co-authorship networks in the research impact: Ego network analyses from Microsoft Academic Search

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  • Ortega, José Luis

Abstract

The main objective of this study is to analyze the relationship between research impact and the structural properties of co-author networks. A new bibliographic source, Microsoft Academic Search, is introduced to test its suitability for bibliometric analyses. Citation counts and 500 one-step ego networks were extracted from this engine. Results show that tiny and sparse networks – characterized by a high Betweenness centrality and a high Average path length – achieved more citations per document than dense and compact networks – described by a high Clustering coefficient and a high Average degree. According to disciplinary differences, Mathematics, Social Sciences and Economics & Business are the disciplines with more sparse and tiny networks; while Physics, Engineering and Geosciences are characterized by dense and crowded networks. This suggests that in sparse ego networks, the central author have more control on their collaborators being more selective in their recruitment and concluding that this behaviour has positive implications in the research impact.

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  • Ortega, José Luis, 2014. "Influence of co-authorship networks in the research impact: Ego network analyses from Microsoft Academic Search," Journal of Informetrics, Elsevier, vol. 8(3), pages 728-737.
    • Handle: RePEc:eee:infome:v:8:y:2014:i:3:p:728-737
    DOI: 10.1016/j.joi.2014.07.001
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    Cited by:

    1. Dehdarirad, Tahereh & Nasini, Stefano, 2017. "Research impact in co-authorship networks: a two-mode analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 371-388.
    2. Lu, Wei & Ren, Yan & Huang, Yong & Bu, Yi & Zhang, Yuehan, 2021. "Scientific collaboration and career stages: An ego-centric perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    3. Zhigao Liu & Yimei Yin & Weidong Liu & Michael Dunford, 2015. "Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 135-158, April.
    4. Dinesh Pradhan & Partha Sarathi Paul & Umesh Maheswari & Subrata Nandi & Tanmoy Chakraborty, 2017. "$$C^3$$ C 3 -index: a PageRank based multi-faceted metric for authors’ performance measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 253-273, January.
    5. Wei Wang & Shuo Yu & Teshome Megersa Bekele & Xiangjie Kong & Feng Xia, 2017. "Scientific collaboration patterns vary with scholars’ academic ages," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 329-343, July.
    6. Muhammad Sajid Qureshi & Ali Daud, 2021. "Fine-grained academic rankings: mapping affiliation of the influential researchers with the top ranked HEIs," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8331-8361, October.
    7. Fan, Lingxu & Guo, Lei & Wang, Xinhua & Xu, Liancheng & Liu, Fangai, 2022. "Does the author’s collaboration mode lead to papers’ different citation impacts? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 16(4).
    8. Henning Kroll & Peter Neuhäusler, 2022. "“Formal and informal networkedness among German Academics”: exploring the role of conferences and co-publications in scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6431-6452, November.
    9. Luigi Aldieri & Gennaro Guida & Maxim Kotsemir & Concetto Paolo Vinci, 2019. "An investigation of impact of research collaboration on academic performance in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2003-2040, July.
    10. Samitas, Aristeidis & Kampouris, Elias, 2018. "Empirical investigation of co-authorship in the field of finance: A network perspective," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 235-246.
    11. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
    12. Chengliang Liu & Qinchang Gui, 2016. "Mapping intellectual structures and dynamics of transport geography research: a scientometric overview from 1982 to 2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 159-184, October.
    13. Noémi Gaskó & Rodica Ioana Lung & Mihai Alexandru Suciu, 2016. "A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 613-632, August.
    14. Anne-Wil Harzing, 2016. "Microsoft Academic (Search): a Phoenix arisen from the ashes?," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1637-1647, September.
    15. Tošić, Aleksandar & Vičič, Jernej, 2021. "Use of Benford's law on academic publishing networks," Journal of Informetrics, Elsevier, vol. 15(3).

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