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Predicting scientific success

Citations

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Cited by:

  1. Gen-Chang Hsu & Wei-Jiun Lin & Syuan-Jyun Sun, 2023. "Temporal trends in academic performance and career duration of principal investigators in ecology and evolutionary biology in Taiwan," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3437-3451, June.
  2. Yajie Zhang & Qiang Yu, 2020. "What is the best article publishing strategy for early career scientists?," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 397-408, January.
  3. 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.
  4. 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.
  5. 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.
  6. Hyungjo Hur & Maryam A Andalib & Julie A Maurer & Joshua D Hawley & Navid Ghaffarzadegan, 2017. "Recent trends in the U.S. Behavioral and Social Sciences Research (BSSR) workforce," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-18, February.
  7. 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.
  8. Schreiber, Michael, 2015. "Restricting the h-index to a publication and citation time window: A case study of a timed Hirsch index," Journal of Informetrics, Elsevier, vol. 9(1), pages 150-155.
  9. 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.
  10. Stegehuis, Clara & Litvak, Nelly & Waltman, Ludo, 2015. "Predicting the long-term citation impact of recent publications," Journal of Informetrics, Elsevier, vol. 9(3), pages 642-657.
  11. João A G Moreira & Xiao Han T Zeng & Luís A Nunes Amaral, 2015. "The Distribution of the Asymptotic Number of Citations to Sets of Publications by a Researcher or from an Academic Department Are Consistent with a Discrete Lognormal Model," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-17, November.
  12. Akella, Akhil Pandey & Alhoori, Hamed & Kondamudi, Pavan Ravikanth & Freeman, Cole & Zhou, Haiming, 2021. "Early indicators of scientific impact: Predicting citations with altmetrics," Journal of Informetrics, Elsevier, vol. 15(2).
  13. 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.
  14. 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.
  15. Tohalino, Jorge A.V. & Amancio, Diego R., 2022. "On predicting research grants productivity via machine learning," Journal of Informetrics, Elsevier, vol. 16(2).
  16. 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.
  17. Danielle H. Lee, 2019. "Predicting the research performance of early career scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1481-1504, December.
  18. Hu, Ya-Han & Tai, Chun-Tien & Liu, Kang Ernest & Cai, Cheng-Fang, 2020. "Identification of highly-cited papers using topic-model-based and bibliometric features: the consideration of keyword popularity," Journal of Informetrics, Elsevier, vol. 14(1).
  19. 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.
  20. Dimitris Bertsimas & Erik Brynjolfsson & Shachar Reichman & John Silberholz, 2015. "OR Forum—Tenure Analytics: Models for Predicting Research Impact," Operations Research, INFORMS, vol. 63(6), pages 1246-1261, December.
  21. Batista-Jr, Antônio de Abreu & Gouveia, Fábio Castro & Mena-Chalco, Jesús P., 2021. "Predicting the Q of junior researchers using data from the first years of publication," Journal of Informetrics, Elsevier, vol. 15(2).
  22. 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).
  23. Matthias Kuppler, 2022. "Predicting the future impact of Computer Science researchers: Is there a gender bias?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6695-6732, November.
  24. Peter Loos & Peter Mertens & Torsten Eymann & Rudy Hirschheim & Burkhard Schwenker & Thomas Hess, 2013. "Qualification Profile of University Professors in Business and Information Systems Engineering (BISE)," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(2), pages 107-114, April.
  25. 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.
  26. Mike Thelwall & Kayvan Kousha, 2021. "Researchers’ attitudes towards the h-index on Twitter 2007–2020: criticism and acceptance," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5361-5368, June.
  27. Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
  28. Mignon Wuestman & Koen Frenken & Iris Wanzenböck, 2020. "A genealogical approach to academic success," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
  29. 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.
  30. Jordan D Dworkin & Russell T Shinohara & Danielle S Bassett, 2019. "The emergent integrated network structure of scientific research," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-17, April.
  31. 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.
  32. 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.
  33. Yuhao Zhou & Ruijie Wang & An Zeng, 2022. "Predicting the impact and publication date of individual scientists’ future papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1867-1882, April.
  34. Wumei Du & Zheng Xie & Yiqin Lv, 2021. "Predicting publication productivity for authors: Shallow or deep architecture?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5855-5879, July.
  35. Petersen, Alexander M. & Pan, Raj K. & Pammolli, Fabio & Fortunato, Santo, 2019. "Methods to account for citation inflation in research evaluation," Research Policy, Elsevier, vol. 48(7), pages 1855-1865.
  36. Yin, Yian & Wang, Dashun, 2017. "The time dimension of science: Connecting the past to the future," Journal of Informetrics, Elsevier, vol. 11(2), pages 608-621.
  37. Pablo Diniz Batista & Igor Marques-Carneiro & Leduc Hermeto de Almeida Fauth & Márcia de Oliveira Reis Brandão, 2018. "Web of Science: Showing a Bug Today That Can Mislead Scientific Research Output Prediction," SAGE Open, , vol. 8(1), pages 21582440187, February.
  38. Ziqiang Zeng & Lantian Shi, 2021. "A two-dimensional journal classification method based on output and input factors: perspectives from citation and authorship related indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3929-3964, May.
  39. Miguel A. García-Pérez, 2013. "Limited validity of equations to predict the future h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 901-909, September.
  40. 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.
  41. 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.
  42. Cao, Xuanyu & Chen, Yan & Ray Liu, K.J., 2016. "A data analytic approach to quantifying scientific impact," Journal of Informetrics, Elsevier, vol. 10(2), pages 471-484.
  43. Brett Mensh & Konrad Kording, 2017. "Ten simple rules for structuring papers," PLOS Computational Biology, Public Library of Science, vol. 13(9), pages 1-9, September.
  44. 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.
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