IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v11y2017i1p307-323.html
   My bibliography  Save this article

Standing on the shoulders of giants

Author

Listed:
  • Amjad, Tehmina
  • Ding, Ying
  • Xu, Jian
  • Zhang, Chenwei
  • Daud, Ali
  • Tang, Jie
  • Song, Min

Abstract

Young scholars in academia often seek to work in collaboration with top researchers in their field in pursuit of a successful career. While success in academia can be defined differently, everyone agrees that training with a well-known researcher can help lead to an efficacious career. This study aims to investigate whether collaborating with established scientists does, in fact, improve junior scholars’ chances of success. If not, what makes young scientists soar in their academic careers? We investigate this question by analyzing the effect of collaboration with a known-star on success of a young scholar. The results suggest that working with leading experts can lead to a successful career, but that it is not the only way. Researchers who were not fortunate enough to start their career with an elite researcher could still succeed through hard work and passion. These findings emerged from analyses of two discrete sets of well-known scholars on the career of newcomers, suggesting their strength and validity.

Suggested Citation

  • Amjad, Tehmina & Ding, Ying & Xu, Jian & Zhang, Chenwei & Daud, Ali & Tang, Jie & Song, Min, 2017. "Standing on the shoulders of giants," Journal of Informetrics, Elsevier, vol. 11(1), pages 307-323.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:1:p:307-323
    DOI: 10.1016/j.joi.2017.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157716302942
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2017.01.004?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. Ebadi, Ashkan & Schiffauerova, Andrea, 2015. "How to become an important player in scientific collaboration networks?," Journal of Informetrics, Elsevier, vol. 9(4), pages 809-825.
    2. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    3. Ali Daud & Muhammad Ahmad & M. S. I. Malik & Dunren Che, 2015. "Using machine learning techniques for rising star prediction in co-author network," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1687-1711, February.
    4. Vicki (Baker) Sweitzer, 2009. "Towards a Theory of Doctoral Student Professional Identity Development: A Developmental Networks Approach," The Journal of Higher Education, Taylor & Francis Journals, vol. 80(1), pages 1-33, January.
    5. Kaur, Jasleen & Ferrara, Emilio & Menczer, Filippo & Flammini, Alessandro & Radicchi, Filippo, 2015. "Quality versus quantity in scientific impact," Journal of Informetrics, Elsevier, vol. 9(4), pages 800-808.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianlin Zhou & An Zeng & Ying Fan & Zengru Di, 2018. "Identifying important scholars via directed scientific collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1327-1343, March.
    2. Tehmina Amjad & Nafeesa Shahid & Ali Daud & Asma Khatoon, 2022. "Citation burst prediction in a bibliometric network," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2773-2790, May.
    3. Samreen Ayaz & Nayyer Masood & Muhammad Arshad Islam, 2018. "Predicting scientific impact based on h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 993-1010, March.
    4. Lubna Zafar & Nayyer Masood & Samreen Ayaz, 2023. "Impact of field of study (FoS) on authors’ citation trend," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2557-2576, April.
    5. Li Hou & Qiang Wu & Yundong Xie, 2022. "Does early publishing in top journals really predict long-term scientific success in the business field?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6083-6107, November.
    6. Lu, Chao & Bu, Yi & Dong, Xianlei & Wang, Jie & Ding, Ying & Larivière, Vincent & Sugimoto, Cassidy R. & Paul, Logan & Zhang, Chengzhi, 2019. "Analyzing linguistic complexity and scientific impact," Journal of Informetrics, Elsevier, vol. 13(3), pages 817-829.
    7. Shen, Hongquan & Cheng, Ying & Ju, Xiufang & Xie, Juan, 2022. "Rethinking the effect of inter-gender collaboration on research performance for scholars," Journal of Informetrics, Elsevier, vol. 16(4).
    8. Kong, Xiangjie & Mao, Mengyi & Jiang, Huizhen & Yu, Shuo & Wan, Liangtian, 2019. "How does collaboration affect researchers’ positions in co-authorship networks?," Journal of Informetrics, Elsevier, vol. 13(3), pages 887-900.
    9. Ali Daud & Min Song & Malik Khizar Hayat & Tehmina Amjad & Rabeeh Ayaz Abbasi & Hassan Dawood & Anwar Ghani, 2020. "Finding rising stars in bibliometric networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 633-661, July.
    10. Jiaying Liu & Tao Tang & Xiangjie Kong & Amr Tolba & Zafer AL-Makhadmeh & Feng Xia, 2018. "Understanding the advisor–advisee relationship via scholarly data analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 161-180, July.
    11. Shuo Xu & Mengjia An & Xin An, 2021. "Do scientific publications by editorial board members have shorter publication delays and then higher influence?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6697-6713, August.
    12. Xie, Qing & Zhang, Xinyuan & Kim, Giyeong & Song, Min, 2022. "Exploring the influence of coauthorship with top scientists on researchers’ affiliation, research topic, productivity, and impact," Journal of Informetrics, Elsevier, vol. 16(3).
    13. Jun Zhang & Yan Hu & Zhaolong Ning & Amr Tolba & Elsayed Elashkar & Feng Xia, 2018. "AIRank: Author Impact Ranking through Positions in Collaboration Networks," Complexity, Hindawi, vol. 2018, pages 1-16, June.
    14. Wang, Wei & Ren, Jing & Alrashoud, Mubarak & Xia, Feng & Mao, Mengyi & Tolba, Amr, 2020. "Early-stage reciprocity in sustainable scientific collaboration," Journal of Informetrics, Elsevier, vol. 14(3).
    15. 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.
    16. Xiomara S. Q. Chacon & Thiago C. Silva & Diego R. Amancio, 2020. "Comparing the impact of subfields in scientific journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 625-639, October.
    17. Mariia Petryk & Michael Rivera & Siddharth Bhattacharya & Liangfei Qiu & Subodha Kumar, 2022. "How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation," Information Systems Research, INFORMS, vol. 33(4), pages 1467-1489, December.
    18. Li, Xin & Tang, Xuli, 2021. "Characterizing interdisciplinarity in drug research: A translational science perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    19. Tehmina Amjad & Javeria Munir, 2021. "Investigating the impact of collaboration with authority authors: a case study of bibliographic data in field of philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4333-4353, May.
    20. Klemiński, Rajmund & Kazienko, Przemyslaw & Kajdanowicz, Tomasz, 2021. "Where should I publish? Heterogeneous, networks-based prediction of paper’s citation success," Journal of Informetrics, Elsevier, vol. 15(3).
    21. Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.

    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. Jorge A. V. Tohalino & Laura V. C. Quispe & Diego R. Amancio, 2021. "Analyzing the relationship between text features and grants productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4255-4275, May.
    2. Mengjiao Qi & An Zeng & Menghui Li & Ying Fan & Zengru Di, 2017. "Standing on the shoulders of giants: the effect of outstanding scientists on young collaborators’ careers," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1839-1850, June.
    3. Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.
    4. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.
    5. Martin Ricker, 2017. "Letter to the Editor: About the quality and impact of scientific articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1851-1855, June.
    6. Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
    7. Shahd Al-Janabi & Lee Wei Lim & Luca Aquili, 2021. "Development of a tool to accurately predict UK REF funding allocation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8049-8062, September.
    8. Etienne Farvaque & Frédéric Gannon, 2018. "Profiling giants: the networks and influence of Buchanan and Tullock," Public Choice, Springer, vol. 175(3), pages 277-302, June.
    9. Hao Liao & Rui Xiao & Giulio Cimini & Matúš Medo, 2014. "Network-Driven Reputation in Online Scientific Communities," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-18, December.
    10. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    11. Jakub Rybacki & Dobromił Serwa, 2021. "What Makes a Successful Scientist in a Central Bank? Evidence From the RePEc Database," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(3), pages 331-357, September.
    12. Schreiber, Michael, 2013. "How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index," Journal of Informetrics, Elsevier, vol. 7(2), pages 325-329.
    13. Álvarez-Bornstein, Belén & Bordons, María, 2021. "Is funding related to higher research impact? Exploring its relationship and the mediating role of collaboration in several disciplines," Journal of Informetrics, Elsevier, vol. 15(1).
    14. Yubing Nie & Yifan Zhu & Qika Lin & Sifan Zhang & Pengfei Shi & Zhendong Niu, 2019. "Academic rising star prediction via scholar’s evaluation model and machine learning techniques," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 461-476, August.
    15. Tóth, István & Lázár, Zsolt I. & Varga, Levente & Járai-Szabó, Ferenc & Papp, István & Florian, Răzvan V. & Ercsey-Ravasz, Mária, 2021. "Mitigating ageing bias in article level metrics using citation network analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    16. Lisa Geraci & Steve Balsis & Alexander J. Busch Busch, 2015. "Gender and the h index in psychology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2023-2034, December.
    17. Tobias Mistele & Tom Price & Sabine Hossenfelder, 2019. "Predicting authors’ citation counts and h-indices with a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 87-104, July.
    18. Anahita Hajibabaei & Andrea Schiffauerova & Ashkan Ebadi, 2023. "Women and key positions in scientific collaboration networks: analyzing central scientists’ profiles in the artificial intelligence ecosystem through a gender lens," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1219-1240, February.
    19. Hugo Horta & Shihui Feng & João M. Santos, 2022. "Homophily in higher education research: a perspective based on co-authorships," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 523-543, January.
    20. Abramo, Giovanni & D'Angelo, CiriacoAndrea & Di Costa, Flavia, 2024. "The moderating role of personal characteristics of authors in the publications’ quality for quantity trade-off," Journal of Informetrics, Elsevier, vol. 18(1).

    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:eee:infome:v:11:y:2017:i:1:p:307-323. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.