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Characterization, description, and considerations for the use of funding acknowledgement data in Web of Science

Citations

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Cited by:

  1. Cristian Mejia & Yuya Kajikawa, 2018. "Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 883-904, March.
  2. Maia Chankseliani, 2023. "Who funds the production of globally visible research in the Global South?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 783-801, January.
  3. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
  4. Heather Keathley-Herring & Eileen Van Aken & Fernando Gonzalez-Aleu & Fernando Deschamps & Geert Letens & Pablo Cardenas Orlandini, 2016. "Assessing the maturity of a research area: bibliometric review and proposed framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 927-951, November.
  5. Marianne Duquenne & Hélène Prost & Joachim Schöpfel & Franck Dumeignil, 2020. "Open Bioeconomy—A Bibliometric Study on the Accessibility of Articles in the Field of Bioeconomy," Publications, MDPI, vol. 8(4), pages 1-33, December.
  6. Daniela Filippo & Pablo Sastrón-Toledo, 2023. "Influence of research on open science in the public policy sphere," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1995-2017, March.
  7. Shu-Hao Chang, 2018. "A pilot study on the connection between scientific fields and patent classification systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 951-970, March.
  8. Zhao, Star X. & Tan, Alice M. & Yu, Shuang & Xu, Xin, 2018. "Analyzing the research funding in physics: The perspective of production and collaboration at institution level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 662-674.
  9. 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.
  10. Weishu Liu & Li Tang & Guangyuan Hu, 2020. "Funding information in Web of Science: an updated overview," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1509-1524, March.
  11. Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
  12. Pengfei Jia & Weixi Xie & Guangyao Zhang & Xianwen Wang, 2023. "Do reviewers get their deserved acknowledgments from the authors of manuscripts?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5687-5703, October.
  13. Alberto Baccini & Eugenio Petrovich, 2022. "Normative versus strategic accounts of acknowledgment data: The case of the top-five journals of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 603-635, January.
  14. Adelaide Martins & Manuel Castelo Branco & Pedro Novo Melo & Carolina Machado, 2022. "Sustainability in Small and Medium-Sized Enterprises: A Systematic Literature Review and Future Research Agenda," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
  15. Christine Meschede, 2020. "The Sustainable Development Goals in Scientific Literature: A Bibliometric Overview at the Meta-Level," Sustainability, MDPI, vol. 12(11), pages 1-14, June.
  16. Katherine W. McCain, 2018. "Beyond Garfield’s Citation Index: an assessment of some issues in building a personal name Acknowledgments Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 605-631, February.
  17. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
  18. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
  19. Lili Miao & Vincent Larivi`ere & Feifei Wang & Yong-Yeol Ahn & Cassidy R. Sugimoto, 2023. "Cooperation and interdependence in global science funding," Papers 2308.08630, arXiv.org, revised Feb 2024.
  20. Erjia Yan & Chaojiang Wu & Min Song, 2018. "The funding factor: a cross-disciplinary examination of the association between research funding and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 369-384, April.
  21. Paul-Hus, Adèle & Mongeon, Philippe & Sainte-Marie, Maxime & Larivière, Vincent, 2017. "The sum of it all: Revealing collaboration patterns by combining authorship and acknowledgements," Journal of Informetrics, Elsevier, vol. 11(1), pages 80-87.
  22. Belén Álvarez-Bornstein & Fernanda Morillo & María Bordons, 2017. "Funding acknowledgments in the Web of Science: completeness and accuracy of collected data," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1793-1812, September.
  23. Liu, Weishu, 2021. "Caveats for the use of Web of Science Core Collection in old literature retrieval and historical bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
  24. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
  25. Star X. Zhao & Wen Lou & Alice M. Tan & Shuang Yu, 2018. "Do funded papers attract more usage?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 153-168, April.
  26. Weishu Liu, 2020. "Accuracy of funding information in Scopus: a comparative case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 803-811, July.
  27. Min Song & Keun Young Kang & Tatsawan Timakum & Xinyuan Zhang, 2020. "Examining influential factors for acknowledgements classification using supervised learning," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-21, February.
  28. Nina Smirnova & Philipp Mayr, 2023. "A comprehensive analysis of acknowledgement texts in Web of Science: a case study on four scientific domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 709-734, January.
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