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How does academic education background affect top researchers’ performance? Evidence from the field of artificial intelligence

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  • Wu, Jiang
  • Ou, Guiyan
  • Liu, Xiaohui
  • Dong, Ke

Abstract

The early academic beginning is critical in the development of a researcher's academic career because it helps determine one's further success. We aim to shed light on the path that drives the success of talents in the field of artificial intelligence (AI) by investigating the academic education background of distinguished AI researchers and analyzing the contribution of different educational factors to their research performance. In this study, we collected and coded the curriculum vitae of 1832 AI researchers. Results show that most AI researchers were educated in the United States and obtained their highest degrees from top universities. As for their educational background, approximately 18.27% of AI researchers chose non-AI majors, such as mathematics, physics, and chemistry, instead of AI-related majors, such as computer science. Furthermore, negative binomial regression analysis demonstrates that individuals who publish more during study period will have better research output, whether they are currently in academia or industry. Researchers in academia with overseas degrees published more articles than those without overseas degrees. In terms of interdisciplinary education, a mathematics background leads to increased research visibility of AI researchers in the industry but depresses the scholarly productivity of AI researchers in academia. Academic qualification is the main factor determining the scientific performance of AI researchers in industry, which is not the case in academia. The analysis also showed that individuals who graduated from more prestigious universities tended to receive more citations than those graduating from less famous universities. Moreover, AI researchers in academia who have graduated from prestigious universities seem to pay more attention to the quality of the papers rather than the quantity.

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  • Wu, Jiang & Ou, Guiyan & Liu, Xiaohui & Dong, Ke, 2022. "How does academic education background affect top researchers’ performance? Evidence from the field of artificial intelligence," Journal of Informetrics, Elsevier, vol. 16(2).
    • Handle: RePEc:eee:infome:v:16:y:2022:i:2:s175115772200044x
    DOI: 10.1016/j.joi.2022.101292
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    as
    1. Beaudry, Catherine & Larivière, Vincent, 2016. "Which gender gap? Factors affecting researchers’ scientific impact in science and medicine," Research Policy, Elsevier, vol. 45(9), pages 1790-1817.
    2. Tammy Harris & Joseph M. Hilbe & James W. Hardin, 2014. "Modeling count data with generalized distributions," Stata Journal, StataCorp LP, vol. 14(3), pages 562-579, September.
    3. Hilbe,Joseph M., 2014. "Modeling Count Data," Cambridge Books, Cambridge University Press, number 9781107611252, September.
    4. 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.
    5. Hanna-Mari Puuska, 2010. "Effects of scholar’s gender and professional position on publishing productivity in different publication types. Analysis of a Finnish university," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 419-437, February.
    6. Vincent Larivière & Chaoqun Ni & Yves Gingras & Blaise Cronin & Cassidy R. Sugimoto, 2013. "Bibliometrics: Global gender disparities in science," Nature, Nature, vol. 504(7479), pages 211-213, December.
    7. Shen, Huijun & Coreynen, Wim & Huang, Can, 2022. "Exclusive licensing of university technology: The effects of university prestige, technology transfer offices, and academy-industry collaboration," Research Policy, Elsevier, vol. 51(1).
    8. Vinod Mishra & Russell Smyth, 2013. "Are more senior academics really more research productive than junior academics? Evidence from Australian law schools," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 411-425, August.
    9. Gonzalez-Brambila, Claudia & Veloso, Francisco M., 2007. "The determinants of research output and impact: A study of Mexican researchers," Research Policy, Elsevier, vol. 36(7), pages 1035-1051, September.
    10. Jacob Biamonte & Peter Wittek & Nicola Pancotti & Patrick Rebentrost & Nathan Wiebe & Seth Lloyd, 2017. "Quantum machine learning," Nature, Nature, vol. 549(7671), pages 195-202, September.
    11. Ángel Borrego & Maite Barrios & Anna Villarroya & Candela Ollé, 2010. "Scientific output and impact of postdoctoral scientists: a gender perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 93-101, April.
    12. Soogwan Doh & Duckhee Jang & Gil†Mo Kang & Dong†Seong Han, 2018. "Research Funding and Performance of Academic Researchers in South Korea," Review of Policy Research, Policy Studies Organization, vol. 35(1), pages 31-60, January.
    13. Pinheiro, Diogo & Melkers, Julia & Youtie, Jan, 2014. "Learning to play the game: Student publishing as an indicator of future scholarly success," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 56-66.
    14. Ho Fai Chan & Benno Torgler, 2015. "The implications of educational and methodological background for the career success of Nobel laureates: an investigation of major awards," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 847-863, January.
    15. Xu, Fang & Ou, Guiyan & Ma, Tingcan & Wang, Xianwen, 2021. "The consistency of impact of preprints and their journal publications," Journal of Informetrics, Elsevier, vol. 15(2).
    16. Rebecca Long & Aleta Crawford & Michael White & Kimberly Davis, 2009. "Determinants of faculty research productivity in information systems: An empirical analysis of the impact of academic origin and academic affiliation," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(2), pages 231-260, February.
    17. A. Baccini & L. Barabesi & M. Cioni & C. Pisani, 2014. "Crossing the hurdle: the determinants of individual scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 2035-2062, December.
    18. Buchmueller, Thomas C. & Dominitz, Jeff & Lee Hansen, W., 1999. "Graduate training and the early career productivity of Ph.D. economists," Economics of Education Review, Elsevier, vol. 18(1), pages 65-77, February.
    19. Fredrik Niclas Piro & Gunnar Sivertsen, 2016. "How can differences in international university rankings be explained?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2263-2278, December.
    20. Shamsul Arifeen Khan Mamun & Mohammad Mafizur Rahman, 2015. "Is there any feedback effect between academic research publication and research collaboration? Evidence from an Australian university," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2179-2196, December.
    21. Flora F. Tien & Robert T. Blackburn, 1996. "Faculty Rank System, Research Motivation, and Faculty Research Productivity: Measure Refinement and Theory Testing," The Journal of Higher Education, Taylor & Francis Journals, vol. 67(1), pages 2-22, January.
    22. Günter Krampen & Ralf Becker & Ute Wahner & Leo Montada, 2007. "On the validity of citation counting in science evaluation: Content analyses of references and citations in psychological publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(2), pages 191-202, May.
    23. Jörg Neufeld, 2016. "Determining effects of individual research grants on publication output and impact: The case of the Emmy Noether Programme (German Research Foundation)," Research Evaluation, Oxford University Press, vol. 25(1), pages 50-61.
    24. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    25. Dietz, James S. & Bozeman, Barry, 2005. "Academic careers, patents, and productivity: industry experience as scientific and technical human capital," Research Policy, Elsevier, vol. 34(3), pages 349-367, April.
    26. Konstantin Fursov & Yana Roschina & Oksana Balmush, 2016. "Determinants of Research Productivity: An Individual-level Lens," Foresight-Russia Форсайт, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 10(2 (eng)), pages 44-56.
    27. Dhillon, Sharanjit Kaur & Ibrahim, Roliana & Selamat, Ali, 2015. "Factors associated with scholarly publication productivity among academic staff: Case of a Malaysian public university," Technology in Society, Elsevier, vol. 42(C), pages 160-166.
    28. Frandsen, Tove Faber & Jacobsen, Rasmus Højbjerg & Wallin, Johan A. & Brixen, Kim & Ousager, Jakob, 2015. "Gender differences in scientific performance: A bibliometric matching analysis of Danish health sciences Graduates," Journal of Informetrics, Elsevier, vol. 9(4), pages 1007-1017.
    29. Weihua Li & Tomaso Aste & Fabio Caccioli & Giacomo Livan, 2019. "Early coauthorship with top scientists predicts success in academic careers," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    30. Konstantin Fursov & Yana Roschina & Oksana Balmush, 2016. "Determinants of Research Productivity: An Individual-level Lens," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(2), pages 44-56.
    31. Andrea Diem & Stefan C. Wolter, 2011. "The Use of Bibliometrics to Measure Research Performance in Education Sciences," Economics of Education Working Paper Series 0066, University of Zurich, Department of Business Administration (IBW), revised May 2013.
    32. Amalia Más-Bleda & Isidro F. Aguillo, 2013. "Can a personal website be useful as an information source to assess individual scientists? The case of European highly cited researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 51-67, July.
    33. Vincent Larivière & Benoit Macaluso & Éric Archambault & Yves Gingras, 2010. "Which scientific elites? On the concentration of research funds, publications and citations," Research Evaluation, Oxford University Press, vol. 19(1), pages 45-53, March.
    34. Sabrina J. Mayer & Justus M. K. Rathmann, 2018. "How does research productivity relate to gender? Analyzing gender differences for multiple publication dimensions," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1663-1693, December.
    35. Jonas Lindahl & Cristian Colliander & Rickard Danell, 2020. "Early career performance and its correlation with gender and publication output during doctoral education," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 309-330, January.
    36. Katarina Prpić, 2002. "Gender and productivity differentials in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(1), pages 27-58, September.
    37. Torger Möller & Marion Schmidt & Stefan Hornbostel, 2016. "Assessing the effects of the German Excellence Initiative with bibliometric methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2217-2239, December.
    38. Yinyu Jin & Sha Yuan & Zhou Shao & Wendy Hall & Jie Tang, 2021. "Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2329-2348, March.
    39. J. Corey Miller & Keith H. Coble & Jayson L. Lusk, 2013. "Evaluating top faculty researchers and the incentives that motivate them," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 519-533, December.
    40. Gobeyn, Sacha & Mouton, Ans M. & Cord, Anna F. & Kaim, Andrea & Volk, Martin & Goethals, Peter L.M., 2019. "Evolutionary algorithms for species distribution modelling: A review in the context of machine learning," Ecological Modelling, Elsevier, vol. 392(C), pages 179-195.
    41. Ming-liang Yue & Rui-nan Li & Gui-yan Ou & Xia Wu & Ting-can Ma, 2020. "An exploration on the flow of leading research talents in China: from the perspective of distinguished young scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1559-1574, November.
    42. Kang, Yankun & Liu, Ruiming, 2021. "Does the merger of universities promote their scientific research performance? Evidence from China," Research Policy, Elsevier, vol. 50(1).
    43. Rørstad, Kristoffer & Aksnes, Dag W., 2015. "Publication rate expressed by age, gender and academic position – A large-scale analysis of Norwegian academic staff," Journal of Informetrics, Elsevier, vol. 9(2), pages 317-333.
    44. Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2014. "Career advancement and scientific performance in universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 891-907, February.
    45. Aliakbar Akbaritabar & Niccolò Casnici & Flaminio Squazzoni, 2018. "The conundrum of research productivity: a study on sociologists in Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 859-882, March.
    46. Sha Yuan & Zhou Shao & Xingxing Wei & Jie Tang & Wendy Hall & Yongli Wang & Ying Wang & Ye Wang, 2020. "Science behind AI: the evolution of trend, mobility, and collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 993-1013, August.
    47. Koen Jonkers & Robert Tijssen, 2008. "Chinese researchers returning home: Impacts of international mobility on research collaboration and scientific productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(2), pages 309-333, November.
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