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Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval

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Cited by:

  1. Chen, Hongshu & Jin, Qianqian & Wang, Ximeng & Xiong, Fei, 2022. "Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
  2. Wei Cheng & Dejun Zheng & Xiaomin Zheng & Huanhuan Ni, 2025. "Combining referenced publication year spectroscopy and topic clustering to identify key knowledge foundations in scientometrics: an analysis of recipients of the Price Award," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 1077-1099, February.
  3. Ichiro WATANABE & Hiroshi SHIMIZU, 2024. "Mainstream Formation and Competitive Dynamics in the Computer Graphics Industry: Topic modeling analysis of US patents," Discussion papers 24018, Research Institute of Economy, Trade and Industry (RIETI).
  4. Huixin Wang & Jing Xie & Shixian Luo & Duy Thong Ta & Qian Wang & Jiao Zhang & Daer Su & Katsunori Furuya, 2023. "Exploring the Interplay between Landscape Planning and Human Well-Being: A Scientometric Review," Land, MDPI, vol. 12(7), pages 1-24, June.
  5. Jung, Sukhwan & Segev, Aviv, 2022. "DAC: Descendant-aware clustering algorithm for network-based topic emergence prediction," Journal of Informetrics, Elsevier, vol. 16(3).
  6. Hengmin Zhu & Li Qian & Wang Qin & Jing Wei & Chao Shen, 2022. "Evolution analysis of online topics based on ‘word-topic’ coupling network," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3767-3792, July.
  7. Yuanrong Zhang & Wei Guo & Jian Ma & Zhonglin Fu & Zhixing Chang & Lei Wang, 2023. "Evolution analysis of cross-domain collaborative research topic: a case study of cognitive-based product conceptual design," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(12), pages 6695-6718, December.
  8. Zhongyi Wang & Jing Chen & Jiangping Chen & Haihua Chen, 2024. "Identifying interdisciplinary topics and their evolution based on BERTopic," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7359-7384, November.
  9. Yating Li & Ye Chen & Qiyu Wang, 2021. "Evolution and diffusion of information literacy topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4195-4224, May.
  10. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
  11. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
  12. Jian Xu & Ying Ding & Yi Bu & Shuqing Deng & Chen Yu & Yimin Zou & Andrew Madden, 2019. "Interdisciplinary scholarly communication: an exploratory study for the field of joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1597-1619, June.
  13. Qiang Gao & Xiao Huang & Ke Dong & Zhentao Liang & Jiang Wu, 2022. "Semantic-enhanced topic evolution analysis: a combination of the dynamic topic model and word2vec," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1543-1563, March.
  14. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
  15. David Doloreux & Jose Gaviria de la Puerta & Iker Pastor-López & Igone Porto Gómez & Borja Sanz & Jon Mikel Zabala-Iturriagagoitia, 2019. "Territorial innovation models: to be or not to be, that’s the question," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1163-1191, September.
  16. 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.
  17. Lukun Zheng & Yuhang Jiang, 2022. "Combining dissimilarity measures for quantifying changes in research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3751-3765, July.
  18. Zhentao Liang & Jin Mao & Kun Lu & Gang Li, 2021. "Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9519-9542, December.
  19. Huichen Gao & Shijuan Wang, 2022. "The Intellectual Structure of Research on Rural-to-Urban Migrants: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(15), pages 1-19, August.
  20. Yosuke Miyata & Emi Ishita & Fang Yang & Michimasa Yamamoto & Azusa Iwase & Keiko Kurata, 2020. "Knowledge structure transition in library and information science: topic modeling and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 665-687, October.
  21. Mario Coccia & Saeed Roshani, 2024. "Evolution of topics and trends in emerging research fields: multiple analyses with entity linking, Mann–Kendall test and burst methods in cloud computing," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5347-5371, September.
  22. Baitong Chen & Ying Ding & Feicheng Ma, 2018. "Semantic word shifts in a scientific domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 211-226, October.
  23. David Chavalarias & Quentin Lobbé & Alexandre Delanoë, 2022. "Draw me Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 545-575, January.
  24. Jinqing Yang & Zhifeng Liu & Yong Huang, 2024. "From informal to formal: scientific knowledge role transition prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4909-4935, August.
  25. Seyyed Reza Taher Harikandeh & Sadegh Aliakbary & Soroush Taheri, 2023. "An embedding approach for analyzing the evolution of research topics with a case study on computer science subdomains," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1567-1582, March.
  26. Mauricio Marrone, 2020. "Application of entity linking to identify research fronts and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 357-379, January.
  27. Qian, Yue & Liu, Yu & Sheng, Quan Z., 2020. "Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence," Journal of Informetrics, Elsevier, vol. 14(3).
  28. Chen, Guo & Hong, Siqi & Du, Chenxin & Wang, Panting & Yang, Zeyu & Xiao, Lu, 2024. "Comparing semantic representation methods for keyword analysis in bibliometric research," Journal of Informetrics, Elsevier, vol. 18(3).
  29. Junsheng Zhang & Xiaoping Sun & Zhihui Liu, 2024. "Measuring the evolving stage of temporal distribution of research topic keyword in scientific literature by research heat curve," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7287-7328, November.
  30. Wang, Xiaoguang & He, Jing & Huang, Han & Wang, Hongyu, 2022. "MatrixSim: A new method for detecting the evolution paths of research topics," Journal of Informetrics, Elsevier, vol. 16(4).
  31. Jung, Sukhwan & Yoon, Wan Chul, 2020. "An alternative topic model based on Common Interest Authors for topic evolution analysis," Journal of Informetrics, Elsevier, vol. 14(3).
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