IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v126y2021i7d10.1007_s11192-020-03687-z.html
   My bibliography  Save this article

Growing with collaboration: footprint of WISE Lab

Author

Listed:
  • Yue Chen

    (Dalian University of Technology)

  • Zhiqi Wang

    (Dalian University of Technology)

  • Kai Song

    (Dalian University of Technology)

  • Deming Lin

    (Dalian University of Technology)

  • Hildrun Kretschmer

    (COLLNET Center)

Abstract

The paper explores the development of WISE Lab during the past 15 years from three complementary perspectives: citation aging characteristics, themes evolution and academic collaboration, based on the research results produced by WISE Lab. The results show that, the half-life of the papers in WISE Lab reaches about 5 years, and the highly cited papers have a longer impact than mainstream papers; WISE Lab is focused on six themes, “Knowledge mapping”, “Visual analysis”, “Scientometrics”, “Patentometrics”, “Information retrieval”, and “Innovation management”, which developed alternately over time; WISE Lab is greatly driven by collaboration, and Prof. Liu contributed in a central way to the team cohesion, his academic spirit and thought influenced widely.

Suggested Citation

  • Yue Chen & Zhiqi Wang & Kai Song & Deming Lin & Hildrun Kretschmer, 2021. "Growing with collaboration: footprint of WISE Lab," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6147-6167, July.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:7:d:10.1007_s11192-020-03687-z
    DOI: 10.1007/s11192-020-03687-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-020-03687-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-020-03687-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wolfgang Glänzel & Henk F. Moed, 2013. "Opinion paper: thoughts and facts on bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 381-394, July.
    2. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    3. Michal Brzezinski, 2015. "Power laws in citation distributions: evidence from Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 213-228, April.
    4. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    5. Wolfgang Glänzel & Bart Thijs & Pei-Shan Chi, 2016. "The challenges to expand bibliometric studies from periodical literature to monographic literature with a new data source: the book citation index," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2165-2179, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Double rank analysis for research assessment," Journal of Informetrics, Elsevier, vol. 12(1), pages 31-41.
    2. Banshal, Sumit Kumar & Gupta, Solanki & Lathabai, Hiran H & Singh, Vivek Kumar, 2022. "Power Laws in altmetrics: An empirical analysis," Journal of Informetrics, Elsevier, vol. 16(3).
    3. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    4. SAITO Yukiko, 2013. "Role of Hub Firms in Geographical Transaction Network," Discussion papers 13080, Research Institute of Economy, Trade and Industry (RIETI).
    5. Liang, Wei & Shi, Yuming & Huang, Qiuling, 2014. "Modeling the Chinese language as an evolving network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 268-276.
    6. Ross Richardson & Matteo G. Richiardi & Michael Wolfson, 2015. "We ran one billion agents. Scaling in simulation models," LABORatorio R. Revelli Working Papers Series 142, LABORatorio R. Revelli, Centre for Employment Studies.
    7. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    8. Harmenberg, Karl, 2024. "A simple theory of Pareto-distributed earnings," Economics Letters, Elsevier, vol. 234(C).
    9. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.
    10. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    11. Kwame Boamah‐Addo & Tomasz J. Kozubowski & Anna K. Panorska, 2023. "A discrete truncated Zipf distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 156-187, May.
    12. A. B. Atkinson, 2017. "Pareto and the Upper Tail of the Income Distribution in the UK: 1799 to the Present," Economica, London School of Economics and Political Science, vol. 84(334), pages 129-156, April.
    13. di Giovanni, Julian & Levchenko, Andrei A. & Rancière, Romain, 2011. "Power laws in firm size and openness to trade: Measurement and implications," Journal of International Economics, Elsevier, vol. 85(1), pages 42-52, September.
    14. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    15. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    16. Yan Qiang & Bo Pei & Weili Wu & Juanjuan Zhao & Xiaolong Zhang & Yue Li & Lidong Wu, 2014. "Improvement of path analysis algorithm in social networks based on HBase," Journal of Combinatorial Optimization, Springer, vol. 28(3), pages 588-599, October.
    17. Taiji Furusawa & Hideo Konishi & Duong Lam Anh Tran, 2020. "International Trade and Income Inequality," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(3), pages 993-1026, July.
    18. Thomas Brenner & Matthias Duschl, 2018. "Modeling Firm and Market Dynamics: A Flexible Model Reproducing Existing Stylized Facts on Firm Growth," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 745-772, October.
    19. Anthony B. Atkinson & Thomas Piketty & Emmanuel Saez, 2011. "Top Incomes in the Long Run of History," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 3-71, March.
    20. Stephanie Rend'on de la Torre & Jaan Kalda & Robert Kitt & Juri Engelbrecht, 2016. "On the topologic structure of economic complex networks: Empirical evidence from large scale payment network of Estonia," Papers 1602.04352, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:126:y:2021:i:7:d:10.1007_s11192-020-03687-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.