A novel approach to predicting exceptional growth in research
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Abstract
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DOI: 10.1371/journal.pone.0239177
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References listed on IDEAS
- Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
Citations
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Cited by:
- Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
- Chavarro, Diego & Taborda, Jaime Andres Perez & Ávila, Alba, 2021. "Connecting brain and heart: artificial intelligence for sustainable development," SocArXiv gj5kr, Center for Open Science.
- Calof, Jonathan & Søilen, Klaus Solberg & Klavans, Richard & Abdulkader, Bisan & Moudni, Ismail El, 2022. "Understanding the structure, characteristics, and future of collective intelligence using local and global bibliometric analyses," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
- Diego Chavarro & Jaime Andrés Perez-Taborda & Alba Ávila, 2022. "Connecting brain and heart: artificial intelligence for sustainable development," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7041-7060, December.
- Wenjie Wei & Hongxu Liu & Zhuanlan Sun, 2022. "Cover papers of top journals are reliable source for emerging topics detection: a machine learning based prediction framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4315-4333, August.
- Yuya Kajikawa, 2022. "Reframing evidence in evidence-based policy making and role of bibliometrics: toward transdisciplinary scientometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5571-5585, September.
- Gozuacik, Necip & Sakar, C. Okan & Ozcan, Sercan, 2023. "Technological forecasting based on estimation of word embedding matrix using LSTM networks," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
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