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Comparison of topic extraction approaches and their results

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Cited by:

  1. Keungoui Kim & Dieter F. Kogler & Sira Maliphol, 2024. "Identifying interdisciplinary emergence in the science of science: combination of network analysis and BERTopic," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
  2. Rob Koopman & Shenghui Wang, 2017. "Mutual information based labelling and comparing clusters," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1157-1167, May.
  3. Mohammed Azmi Al-Betar & Ammar Kamal Abasi & Ghazi Al-Naymat & Kamran Arshad & Sharif Naser Makhadmeh, 2023. "Optimization of scientific publications clustering with ensemble approach for topic extraction," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2819-2877, May.
  4. Michael Rennings & Philipp Baaden & Carolin Block & Marcus John & Stefanie Bröring, 2024. "Assessing emerging sustainability-oriented technologies: the case of precision agriculture," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 2969-2998, June.
  5. A. V. Chumachenko & B. G. Kreminskyi & Iu. L. Mosenkis & A. I. Yakimenko, 2020. "Dynamics of topic formation and quantitative analysis of hot trends in physical science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 739-753, October.
  6. Diana Maynard & Benedetto Lepori & Johann Petrak & Xingyi Song & Philippe Laredo, 2020. "Using ontologies to map between research data and policymakers’ presumptions: the experience of the KNOWMAK project," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1275-1290, November.
  7. Shenghui Wang & Rob Koopman, 2017. "Clustering articles based on semantic similarity," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1017-1031, May.
  8. Shuo Xu & Junwan Liu & Dongsheng Zhai & Xin An & Zheng Wang & Hongshen Pang, 2018. "Overlapping thematic structures extraction with mixed-membership stochastic blockmodel," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 61-84, October.
  9. Alexey Lyutov & Yilmaz Uygun & Marc-Thorsten Hütt, 2021. "Machine learning misclassification of academic publications reveals non-trivial interdependencies of scientific disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1173-1186, February.
  10. Maxime Rivest & Etienne Vignola-Gagné & Éric Archambault, 2021. "Article-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-18, May.
  11. Cassi, Lorenzo & Lahatte, Agénor & Rafols, Ismael & Sautier, Pierre & de Turckheim, Élisabeth, 2017. "Improving fitness: Mapping research priorities against societal needs on obesity," Journal of Informetrics, Elsevier, vol. 11(4), pages 1095-1113.
  12. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
  13. Kevin W. Boyack, 2017. "Investigating the effect of global data on topic detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 999-1015, May.
  14. Frank Havemann & Jochen Gläser & Michael Heinz, 2017. "Memetic search for overlapping topics based on a local evaluation of link communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1089-1118, May.
  15. Samira Ranaei & Arho Suominen & Alan Porter & Stephen Carley, 2020. "Evaluating technological emergence using text analytics: two case technologies and three approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 215-247, January.
  16. Carlos Olmeda-Gómez & Carlos Romá-Mateo & Maria-Antonia Ovalle-Perandones, 2019. "Overview of trends in global epigenetic research (2009–2017)," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1545-1574, June.
  17. Paul Donner, 2021. "Validation of the Astro dataset clustering solutions with external data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1619-1645, February.
  18. Peter Sjögårde & Per Ahlgren & Ludo Waltman, 2021. "Algorithmic labeling in hierarchical classifications of publications: Evaluation of bibliographic fields and term weighting approaches," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 853-869, July.
  19. Zhang, Yi & Lu, Jie & Liu, Feng & Liu, Qian & Porter, Alan & Chen, Hongshu & Zhang, Guangquan, 2018. "Does deep learning help topic extraction? A kernel k-means clustering method with word embedding," Journal of Informetrics, Elsevier, vol. 12(4), pages 1099-1117.
  20. Rob Koopman & Shenghui Wang & Andrea Scharnhorst, 2017. "Contextualization of topics: browsing through the universe of bibliographic information," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1119-1139, May.
  21. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
  22. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
  23. Matthias Held & Grit Laudel & Jochen Gläser, 2021. "Challenges to the validity of topic reconstruction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4511-4536, May.
  24. 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).
  25. Ballester, Omar & Penner, Orion, 2022. "Robustness, replicability and scalability in topic modelling," Journal of Informetrics, Elsevier, vol. 16(1).
  26. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  27. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  28. Christian Weismayer & Ilona Pezenka, 2017. "Identifying emerging research fields: a longitudinal latent semantic keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1757-1785, December.
  29. Theresa Velden & Shiyan Yan & Carl Lagoze, 2017. "Mapping the cognitive structure of astrophysics by infomap clustering of the citation network and topic affinity analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1033-1051, May.
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