IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v21y2019i3d10.1007_s10796-017-9773-z.html
   My bibliography  Save this article

Composing Scientific Collaborations Based on Scholars’ Rank in Hypergraph

Author

Listed:
  • Fahimeh Ghasemian

    (University of Isfahan)

  • Kamran Zamanifar

    (University of Isfahan)

  • Nasser Ghasem-Aghaee

    (University of Isfahan)

Abstract

Finding the right scholars for collaboration is crucial for scientific progress. In this study, a novel algorithm is proposed to find the successful team configurations for scientific collaboration in the presence of the collaboration network of scholars. In this algorithm, the collaboration network is exploited to estimate the trust level among team members and the skill level of the scholars, while a hypergraph is used to model the relations. Also, our algorithm improves the search process by directing it to the promising regions, where the probability of finding the successful teams is high. A comparison with other algorithms is done to evaluate the proposed algorithm, using the similarity to successful collaborations. Our findings show that this algorithm achieves a significantly higher performance, compared to the other algorithms.

Suggested Citation

  • Fahimeh Ghasemian & Kamran Zamanifar & Nasser Ghasem-Aghaee, 2019. "Composing Scientific Collaborations Based on Scholars’ Rank in Hypergraph," Information Systems Frontiers, Springer, vol. 21(3), pages 687-702, June.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:3:d:10.1007_s10796-017-9773-z
    DOI: 10.1007/s10796-017-9773-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-017-9773-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/s10796-017-9773-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. Gert-Jan Vreede & Pedro Antunes & Julita Vassileva & Marco Aurélio Gerosa & Kewen Wu, 2016. "Collaboration technology in teams and organizations: Introduction to the special issue," Information Systems Frontiers, Springer, vol. 18(1), pages 1-6, February.
    2. Hamidreza Eslami & Ashkan Ebadi & Andrea Schiffauerova, 2013. "Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 99-119, October.
    3. Jengchung Victor Chen & I-Han Lu & David C. Yen & Andree E. Widjaja, 0. "Factors affecting the performance of internal control task team in high-tech firms," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    4. Barry Bozeman & Daniel Fay & Catherine Slade, 2013. "Research collaboration in universities and academic entrepreneurship: the-state-of-the-art," The Journal of Technology Transfer, Springer, vol. 38(1), pages 1-67, February.
    5. Yong Sun & Wenan Tan & Lingxia Li & Weiming Shen & Zhuming Bi & Xiaoming Hu, 2016. "A new method to identify collaborative partners in social service provider networks," Information Systems Frontiers, Springer, vol. 18(3), pages 565-578, June.
    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. Fahimeh Ghasemian & Kamran Zamanifar & Nasser Ghasem-Aqaee & Noshir Contractor, 2016. "Toward a better scientific collaboration success prediction model through the feature space expansion," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 777-801, August.
    2. Matthijs J. Verhulst & Anne-Françoise Rutkowski, 2018. "Decision-Making in the Police Work Force: Affordances Explained in Practice," Group Decision and Negotiation, Springer, vol. 27(5), pages 827-852, October.
    3. Liming Zhao & Haihong Zhang & Wenqing Wu, 2019. "Cooperative knowledge creation in an uncertain network environment based on a dynamic knowledge supernetwork," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 657-685, May.
    4. Thomas Hamadi & Jens Leker & Klaus Meerholz, 2018. "Emergence Of Innovation Champions: Differences In The R&D Collaboration Process Between Science And Industry," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(08), pages 1-17, December.
    5. Gibson, Elizabeth & Daim, Tugrul U. & Dabic, Marina, 2019. "Evaluating university industry collaborative research centers," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 181-202.
    6. Toluwase Asubiaro, 2019. "How collaboration type, publication place, funding and author’s role affect citations received by publications from Africa: A bibliometric study of LIS research from 1996 to 2015," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1261-1287, September.
    7. Gianluca Fabiano & Andrea Marcellusi & Giampiero Favato, 2020. "Public–private contribution to biopharmaceutical discoveries: a bibliometric analysis of biomedical research in UK," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 153-168, July.
    8. Jeongeun Kim & Molly Ott & Lindsey Dippold, 2020. "University and Department Influences on Scientists’ Occupational Outcomes," Research in Higher Education, Springer;Association for Institutional Research, vol. 61(2), pages 197-228, March.
    9. Niels Stijn & Frank J. Rijnsoever & Martine Veelen, 2018. "Exploring the motives and practices of university–start-up interaction: evidence from Route 128," The Journal of Technology Transfer, Springer, vol. 43(3), pages 674-713, June.
    10. Taheri, Mozhdeh & van Geenhuizen, Marina, 2016. "Teams' boundary-spanning capacity at university: Performance of technology projects in commercialization," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 31-43.
    11. Gaganmeet Kaur Awal & K. K. Bharadwaj, 2019. "Leveraging collective intelligence for behavioral prediction in signed social networks through evolutionary approach," Information Systems Frontiers, Springer, vol. 21(2), pages 417-439, April.
    12. Sisi Li & Chang Zhu & Shasha Li, 2018. "Student researchers’ perceived prerequisites for voluntary research collaboration in the context of Flemish and Chinese universities," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-19, May.
    13. Harvey Humphrey & Edmund Coleman-Fountain, 2024. "Creating Time for LGBT+ Disabled Youth: Co-production Outside Chrononormativity," Sociological Research Online, , vol. 29(1), pages 233-242, March.
    14. Jung, Jiwon & Bozeman, Barry & Gaughan, Monica, 2017. "Impact of research collaboration cosmopolitanism on job satisfaction," Research Policy, Elsevier, vol. 46(10), pages 1863-1872.
    15. Li, Feng & Miao, Yajun & Yang, Chenchen, 2015. "How do alumni faculty behave in research collaboration? An analysis of Chang Jiang Scholars in China," Research Policy, Elsevier, vol. 44(2), pages 438-450.
    16. Ingvild Reymert & Taran Thune, 2023. "Task complementarity in academic work: a study of the relationship between research, education and third mission tasks among university professors," The Journal of Technology Transfer, Springer, vol. 48(1), pages 331-360, February.
    17. Elizabeth A. Corley & Barry Bozeman & Xuefan Zhang & Chin-Chang Tsai, 2019. "The expanded scientific and technical human capital model: the addition of a cultural dimension," The Journal of Technology Transfer, Springer, vol. 44(3), pages 681-699, June.
    18. Sanaa Zebakh & Ali Rhouma & Fabrice Dentressangle & Maurice Héral & Sadiki Mohammed & Florence Jacquet, 2024. "To what extent the ARIMNet transnational programme has contributed to the implementation of the Euro-Mediterranean research and innovation area?," Post-Print hal-04102527, HAL.
    19. Fernando Martin-Alcazar & Marta Ruiz-Martinez & Gonzalo Sanchez-Gardey, 2019. "Social Capital and Academic Research Performance: A Conceptual Model Proposal," International Journal of Business Administration, International Journal of Business Administration, Sciedu Press, vol. 10(2), pages 22-31, March.
    20. Yong Sun & Wenan Tan, 2020. "Combining Spatial Optimization and Multi-Agent Temporal Difference Learning for Task Assignment in Uncertain Crowdsourcing," Information Systems Frontiers, Springer, vol. 22(6), pages 1447-1465, December.

    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:infosf:v:21:y:2019:i:3:d:10.1007_s10796-017-9773-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.