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Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?

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. Leo Capari & Harald Wilfing & Andreas Exner & Thomas Höflehner & Daniela Haluza, 2022. "Cooling the City? A Scientometric Study on Urban Green and Blue Infrastructure and Climate Change-Induced Public Health Effects," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
  3. 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).
  4. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
  5. Mike Thelwall, 2019. "Are classic references cited first? An analysis of citation order within article sections," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 723-731, August.
  6. Evi Steelyana W. & Nur Afiah Nunuy & Dewi Nanny & Wahyuni Ersa Tri & Avianti Ilya, 2024. "Policy Strategies for Public–Private Partnership on Broadband Infrastructure: A Systematic Literature Review," Central European Journal of Public Policy, Sciendo, vol. 18(1), pages 1-23.
  7. Annarelli, Alessandro & Battistella, Cinzia & Nonino, Fabio & Parida, Vinit & Pessot, Elena, 2021. "Literature review on digitalization capabilities: Co-citation analysis of antecedents, conceptualization and consequences," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  8. 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.
  9. Dewan F. Wahid & Elkafi Hassini, 2022. "A Literature Review on Correlation Clustering: Cross-disciplinary Taxonomy with Bibliometric Analysis," SN Operations Research Forum, Springer, vol. 3(3), pages 1-42, September.
  10. Giulio Giacomo Cantone, 2024. "How to measure interdisciplinary research? A systemic design for the model of measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4937-4982, August.
  11. Kai Nishikawa, 2023. "How and why are citations between disciplines made? A citation context analysis focusing on natural sciences and social sciences and humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2975-2997, May.
  12. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Discontinuities in citation relations among journals: self-organized criticality as a model of scientific revolutions and change," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 623-644, July.
  13. 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.
  14. Pei-Shan Chi & Stijn Conix, 2022. "Measuring the isolation of research topics in philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1669-1696, April.
  15. Alexandre Truc, 2022. "The Disciplinary Mobility of Core Behavioral Economists," GREDEG Working Papers 2022-27, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
  16. Yousif Elsamani & Yuya Kajikawa, 2024. "Envisioning the Future of Mobility: A Well-Being-Oriented Approach," Sustainability, MDPI, vol. 16(18), pages 1-22, September.
  17. Haunschild, Robin & Daniels, Angela D. & Bornmann, Lutz, 2022. "Scores of a specific field-normalized indicator calculated with different approaches of field-categorization: Are the scores different or similar?," Journal of Informetrics, Elsevier, vol. 16(1).
  18. Mejía, Cristian & Kajikawa, Yuya, 2019. "Technology news and their linkage to production of knowledge in robotics research," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 114-124.
  19. Fang Han & Christopher L. Magee, 2018. "Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 767-796, August.
  20. Sitaram Devarakonda & Dmitriy Korobskiy & Tandy Warnow & George Chacko, 2020. "Viewing computer science through citation analysis: Salton and Bergmark Redux," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 271-287, October.
  21. Luis Araya-Castillo & Felipe Hernández-Perlines & Hugo Moraga & Antonio Ariza-Montes, 2021. "Scientometric Analysis of Research on Socioemotional Wealth," Sustainability, MDPI, vol. 13(7), pages 1-26, March.
  22. Shome, Samik & Hassan, M. Kabir & Verma, Sushma & Panigrahi, Tushar Ranjan, 2023. "Impact investment for sustainable development: A bibliometric analysis," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 770-800.
  23. Rongrong Li & Xuefeng Wang, 2019. "Imbalances between the Quantity and Quality of China’s Solar Energy Research," Sustainability, MDPI, vol. 11(3), pages 1-15, January.
  24. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Zhang, Lin, 2018. "A comparison of two approaches for measuring interdisciplinary research output: The disciplinary diversity of authors vs the disciplinary diversity of the reference list," Journal of Informetrics, Elsevier, vol. 12(4), pages 1182-1193.
  25. Li, Menghui & Yang, Liying & Zhang, Huina & Shen, Zhesi & Wu, Chensheng & Wu, Jinshan, 2017. "Do mathematicians, economists and biomedical scientists trace large topics more strongly than physicists?," Journal of Informetrics, Elsevier, vol. 11(2), pages 598-607.
  26. Mejia, Cristian & Kajikawa, Yuya, 2020. "Emerging topics in energy storage based on a large-scale analysis of academic articles and patents," Applied Energy, Elsevier, vol. 263(C).
  27. Mariana-Daniela González-Zamar & Emilio Abad-Segura, 2021. "Emotional Creativity in Art Education: An Exploratory Analysis and Research Trends," IJERPH, MDPI, vol. 18(12), pages 1-20, June.
  28. Lucie Beranová & Marcin P. Joachimiak & Tomáš Kliegr & Gollam Rabby & Vilém Sklenák, 2022. "Why was this cited? Explainable machine learning applied to COVID-19 research literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2313-2349, May.
  29. 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.
  30. 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.
  31. Paul Donner, 2021. "Validation of the Astro dataset clustering solutions with external data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1619-1645, February.
  32. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
  33. 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.
  34. María de la Cruz del Río-Rama & Claudia Patricia Maldonado-Erazo & José Álvarez-García & Amador Durán-Sánchez, 2020. "Cultural and Natural Resources in Tourism Island: Bibliometric Mapping," Sustainability, MDPI, vol. 12(2), pages 1-26, January.
  35. Loet Leydesdorff & Inga Ivanova, 2021. "The measurement of “interdisciplinarity” and “synergy” in scientific and extra‐scientific collaborations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 387-402, April.
  36. Yuanyuan Liu & Qiang Wu & Shijie Wu & Yong Gao, 2021. "Weighted citation based on ranking-related contribution: a new index for evaluating article impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8653-8672, October.
  37. 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.
  38. Zhang, Yi & Wu, Mengjia & Miao, Wen & Huang, Lu & Lu, Jie, 2021. "Bi-layer network analytics: A methodology for characterizing emerging general-purpose technologies," Journal of Informetrics, Elsevier, vol. 15(4).
  39. Mike Thelwall & Kayvan Kousha & Mahshid Abdoli & Emma Stuart & Meiko Makita & Paul Wilson & Jonathan Levitt, 2023. "Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 582-593, May.
  40. Sukrit Vinayavekhin & Feng Li & Aneesh Banerjee & Andrea Caputo, 2023. "The academic landscape of sustainability in management literature: Towards a more interdisciplinary research agenda," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5748-5784, December.
  41. Lin Zhang & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
  42. Giovanni Colavizza & Iain Hrynaszkiewicz & Isla Staden & Kirstie Whitaker & Barbara McGillivray, 2020. "The citation advantage of linking publications to research data," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-18, April.
  43. Haunschild, Robin & Schier, Hermann & Marx, Werner & Bornmann, Lutz, 2018. "Algorithmically generated subject categories based on citation relations: An empirical micro study using papers on overall water splitting," Journal of Informetrics, Elsevier, vol. 12(2), pages 436-447.
  44. Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
  45. Takahiro Kawamura & Katsutaro Watanabe & Naoya Matsumoto & Shusaku Egami & Mari Jibu, 2018. "Funding map using paragraph embedding based on semantic diversity," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 941-958, August.
  46. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
  47. Gerson Pech & Catarina Delgado & Silvio Paolo Sorella, 2022. "Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1513-1528, November.
  48. Cristian Mejia & Yuya Kajikawa, 2021. "The Academic Landscapes of Manufacturing Enterprise Performance and Environmental Sustainability: A Study of Commonalities and Differences," IJERPH, MDPI, vol. 18(7), pages 1-16, March.
  49. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
  50. 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).
  51. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
  52. Fei Shu & Yue Ma & Junping Qiu & Vincent Larivière, 2020. "Classifications of science and their effects on bibliometric evaluations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2727-2744, December.
  53. Hector O. Zapata & Supratik Mukhopadhyay, 2022. "A Bibliometric Analysis of Machine Learning Econometrics in Asset Pricing," JRFM, MDPI, vol. 15(11), pages 1-17, November.
  54. Claudia Patricia Maldonado-Erazo & José Álvarez-García & María de la Cruz del Río-Rama & Amador Durán-Sánchez, 2021. "Scientific Mapping on the Impact of Climate Change on Cultural and Natural Heritage: A Systematic Scientometric Analysis," Land, MDPI, vol. 10(1), pages 1-19, January.
  55. Yan-Li Liu & Wen-Juan Yuan & Shao-Hong Zhu, 2022. "The state of social science research on COVID-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 369-383, January.
  56. Ballester, Omar & Penner, Orion, 2022. "Robustness, replicability and scalability in topic modelling," Journal of Informetrics, Elsevier, vol. 16(1).
  57. Elisabeth S. C. Berger & Christine Blanka, 2024. "Comprehensive and multifaceted perspectives on sustainability, urban studies, and entrepreneurship," Small Business Economics, Springer, vol. 62(2), pages 471-501, February.
  58. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
  59. 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.
  60. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
  61. June Young Lee & Sejung Ahn & Dohyun Kim, 2021. "Deep learning-based prediction of future growth potential of technologies," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
  62. Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.
  63. Lutz Bornmann & Alexander Tekles & Loet Leydesdorff, 2019. "How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1187-1205, May.
  64. Alfonso Ávila-Robinson & Cristian Mejia & Shintaro Sengoku, 2021. "Are bibliometric measures consistent with scientists’ perceptions? The case of interdisciplinarity in research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7477-7502, September.
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