IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v557y2020ics037843712030501x.html
   My bibliography  Save this article

Scholar’s career switch adhesive with research topics: An evidence from China

Author

Listed:
  • Ma, Yinghong
  • Song, Le
  • Ji, Zhaoxun
  • Wang, Qian
  • Yu, Qinglin

Abstract

Despite persistent efforts in untangling the mechanism of scientists switching between research topics, little is investigated for the relationship of scholars’ career stage switch leading to dynamics of research topics. In this paper, aiming to reveal career stage and its influence on research topics, we construct a two-layer network model, coauthors collaboration network (α-layer) for scholars research career stages and papers similarity network (β-layer) for research topic types, and analyze the relationship between the career stage switch and the topic type change. Applying the data set SMSEC from China to the model, the different statistics of the two layers show different forming mechanisms, the preference attachment and the rule of similarity inherited in the two layers, respectively. The coupling mechanism of the two layers is displayed by correlation of career stages and topic types, and presented by a framework with contributions of new added papers and associated scholars. The results show that the longer of research career is, the bigger contribution on the type of divided topics is; a scholar with large topic scopes would more likely insist in his/her research.

Suggested Citation

  • Ma, Yinghong & Song, Le & Ji, Zhaoxun & Wang, Qian & Yu, Qinglin, 2020. "Scholar’s career switch adhesive with research topics: An evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    • Handle: RePEc:eee:phsmap:v:557:y:2020:i:c:s037843712030501x
    DOI: 10.1016/j.physa.2020.124959
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712030501X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2020.124959?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. Gajewski, Ł.G. & Suchecki, K. & Hołyst, J.A., 2019. "Multiple propagation paths enhance locating the source of diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 34-41.
    2. Iina Hellsten & Renaud Lambiotte & Andrea Scharnhorst & Marcel Ausloos, 2007. "Self-citations, co-authorships and keywords: A new approach to scientists’ field mobility?," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(3), pages 469-486, September.
    3. Ali Gazni & Fereshteh Didegah, 2011. "Investigating different types of research collaboration and citation impact: a case study of Harvard University’s publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 251-265, May.
    4. Wang, Jian, 2016. "Knowledge creation in collaboration networks: Effects of tie configuration," Research Policy, Elsevier, vol. 45(1), pages 68-80.
    5. Belkhouja, Mustapha & Yoon, Hyungseok (David), 2018. "How does openness influence the impact of a scholar’s research? An analysis of business scholars’ citations over their careers," Research Policy, Elsevier, vol. 47(10), pages 2037-2047.
    6. Klavans, Richard & Boyack, Kevin W., 2017. "Research portfolio analysis and topic prominence," Journal of Informetrics, Elsevier, vol. 11(4), pages 1158-1174.
    7. Chołoniewski, Jan & Sienkiewicz, Julian & Leban, Gregor & Hołyst, Janusz A., 2019. "Modeling of temporal fluctuation scaling in online news network with independent cascade model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 129-144.
    8. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    9. An Zeng & Zhesi Shen & Jianlin Zhou & Ying Fan & Zengru Di & Yougui Wang & H. Eugene Stanley & Shlomo Havlin, 2019. "Increasing trend of scientists to switch between topics," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    10. Li, Eldon Y. & Liao, Chien Hsiang & Yen, Hsiuju Rebecca, 2013. "Co-authorship networks and research impact: A social capital perspective," Research Policy, Elsevier, vol. 42(9), pages 1515-1530.
    11. Radhamany Sooryamoorthy, 2009. "Do types of collaboration change citation? Collaboration and citation patterns of South African science publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 177-193, October.
    12. Tao Jia & Dashun Wang & Boleslaw K. Szymanski, 2017. "Quantifying patterns of research-interest evolution," Nature Human Behaviour, Nature, vol. 1(4), pages 1-7, April.
    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. Song, Le & Ma, Yinghong, 2022. "Evaluating tacit knowledge diffusion with algebra matrix algorithm based social networks," Applied Mathematics and Computation, Elsevier, vol. 428(C).

    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. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
    2. Greta Falavigna & Alessandro Manello, "undated". "Labour productivity and social network metrics in scientific research," CERIS Working Paper 201418, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    3. József Popp & Péter Balogh & Judit Oláh & Sebastian Kot & Mónika Harangi Rákos & Péter Lengyel, 2018. "Social Network Analysis of Scientific Articles Published by Food Policy," Sustainability, MDPI, vol. 10(3), pages 1-20, February.
    4. Xia Fan & Xiaowan Yang & Liming Chen, 2015. "Diversified resources and academic influence: patterns of university–industry collaboration in Chinese research-oriented universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(2), pages 489-509, August.
    5. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    6. Zhang, Lin & Qi, Fan & Sivertsen, Gunnar & Liang, Liming & Campbell, David, 2023. "Gender differences in the patterns and consequences of changing specialization in scientific careers," SocArXiv ep5bx, Center for Open Science.
    7. Ping Ni & Xinying An, 2018. "Relationship between international collaboration papers and their citations from an economic perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 863-877, August.
    8. Krzysztof Klincewicz, 2016. "The emergent dynamics of a technological research topic: the case of graphene," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 319-345, January.
    9. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    10. Ali Gazni & Cassidy R. Sugimoto & Fereshteh Didegah, 2012. "Mapping world scientific collaboration: Authors, institutions, and countries," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 323-335, February.
    11. 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.
    12. Lipeng Fan & Yuefen Wang & Shengchun Ding & Binbin Qi, 2020. "Productivity trends and citation impact of different institutional collaboration patterns at the research units’ level," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1179-1196, November.
    13. Li, Eldon Y. & Liao, Chien Hsiang & Yen, Hsiuju Rebecca, 2013. "Co-authorship networks and research impact: A social capital perspective," Research Policy, Elsevier, vol. 42(9), pages 1515-1530.
    14. Tu, Jing, 2020. "The role of dyadic social capital in enhancing collaborative knowledge creation," Journal of Informetrics, Elsevier, vol. 14(2).
    15. Jing Tu, 2019. "What connections lead to good scientific performance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 587-604, February.
    16. 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.
    17. Jongwuk Ahn & Dong-hyun Oh & Jeong-Dong Lee, 2014. "The scientific impact and partner selection in collaborative research at Korean universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 173-188, July.
    18. David Natcher & Ana Maria Bogdan & Angela Lieverse & Kent Spiers, 2020. "Gender and Arctic climate change science in Canada," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-8, December.
    19. Belkhouja, Mustapha & Fattoum, Senda & Yoon, Hyungseok (David), 2021. "Does greater diversification increase individual productivity? The moderating effect of attention allocation," Research Policy, Elsevier, vol. 50(6).
    20. Hongquan Shen & Juan Xie & Jiang Li & Ying Cheng, 2021. "The correlation between scientific collaboration and citation count at the paper level: a meta-analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3443-3470, April.

    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:phsmap:v:557:y:2020:i:c:s037843712030501x. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.