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A topic model approach to measuring interdisciplinarity at the National Science Foundation

Citations

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Cited by:

  1. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
  2. Erin Leahey & Jina Lee & Russell J. Funk, 2023. "What Types of Novelty Are Most Disruptive?," American Sociological Review, , vol. 88(3), pages 562-597, June.
  3. Jingwei Zheng & Ke Zhang & Boya Han & Jiayi Hou, 2023. "Research Interdisciplinarity and Citation Impact: A Network Analysis of Social Networking Sites Research," SAGE Open, , vol. 13(3), pages 21582440231, August.
  4. Lu Huang & Yijie Cai & Erdong Zhao & Shengting Zhang & Yue Shu & Jiao Fan, 2022. "Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6733-6761, November.
  5. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
  6. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
  7. Wullum Nielsen, Mathias & Börjeson, Love, 2019. "Gender diversity in the management field: Does it matter for research outcomes?," Research Policy, Elsevier, vol. 48(7), pages 1617-1632.
  8. Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.
  9. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
  10. Benjamin M. Knisely & Holly H. Pavliscsak, 2023. "Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3197-3224, May.
  11. Schuitema, Geertje & D. Sintov, Nicole, 2017. "Should we quit our jobs? Challenges, barriers and recommendations for interdisciplinary energy research," Energy Policy, Elsevier, vol. 101(C), pages 246-250.
  12. repec:oup:rseval:v:32:y:2024:i:2:p:213-227. is not listed on IDEAS
  13. Zhang, Yi & Zhang, Guangquan & Chen, Hongshu & Porter, Alan L. & Zhu, Donghua & Lu, Jie, 2016. "Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 179-191.
  14. Ran Xu & Navid Ghaffarzadegan, 2018. "Neuroscience bridging scientific disciplines in health: Who builds the bridge, who pays for it?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1183-1204, November.
  15. Hoang-Son Pham & Bram Vancraeynest & Hanne Poelmans & Sadia Vancauwenbergh & Amr Ali-Eldin, 2023. "Identifying interdisciplinary research in research projects," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5521-5544, October.
  16. Leahey, Erin & Barringer, Sondra N., 2020. "Universities’ commitment to interdisciplinary research: To what end?," Research Policy, Elsevier, vol. 49(2).
  17. Jihong Chen & Kai Zhang & Yuan Zhou & Yufei Liu & Lingfeng Li & Zheng Chen & Li Yin, 2019. "Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning," Sustainability, MDPI, vol. 11(12), pages 1-38, June.
  18. David Lenz & Peter Winker, 2020. "Measuring the diffusion of innovations with paragraph vector topic models," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
  19. Xiuwen Chen & Jianping Li & Xiaolei Sun & Dengsheng Wu, 2019. "Early identification of intellectual structure based on co-word analysis from research grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 349-369, October.
  20. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
  21. Hongyu Zhou & Raf Guns & Tim C. E. Engels, 2022. "Are social sciences becoming more interdisciplinary? Evidence from publications 1960–2014," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1201-1221, September.
  22. Jiang, Hanchen & Qiang, Maoshan & Lin, Peng, 2016. "A topic modeling based bibliometric exploration of hydropower research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 226-237.
  23. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
  24. Bethany K & Nicole Motzer & Kelly J, 2023. "Pathway profiles: Learning from five main approaches to assessing interdisciplinarity," Research Evaluation, Oxford University Press, vol. 32(2), pages 213-227.
  25. Yeow Chong Goh & Xin Qing Cai & Walter Theseira & Giovanni Ko & Khiam Aik Khor, 2020. "Evaluating human versus machine learning performance in classifying research abstracts," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1197-1212, November.
  26. Shiyun Wang & Jin Mao & Yujie Cao & Gang Li, 2022. "Integrated knowledge content in an interdisciplinary field: identification, classification, and application," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6581-6614, November.
  27. Zuo, Zhiya & Zhao, Kang, 2018. "The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions," Journal of Informetrics, Elsevier, vol. 12(3), pages 736-756.
  28. Mao, Jin & Liang, Zhentao & Cao, Yujie & Li, Gang, 2020. "Quantifying cross-disciplinary knowledge flow from the perspective of content: Introducing an approach based on knowledge memes," Journal of Informetrics, Elsevier, vol. 14(4).
  29. Andrea Zielinski, 2022. "Impact of model settings on the text-based Rao diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7751-7768, December.
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