Journal of Information Resources Management ›› 2024, Vol. 14 ›› Issue (2): 162-168,封2.doi: 10.13365/j.jirm.2024.02.162

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Application and Reflection of Full-text Bibliometric in the Era of Large Models ——A Review of the 2023 Academic Salon on Full-text Bibliometric Analysis

Zhou Haichen1　Zhang Chengzhi2　Hu Zhigang3　Xu Shuo4　Mao Jin5　Chen Liang6   

  1. 1.National Science Library(Chengdu), Chinese Academy of Sciences, Chengdu, 610299;　
    2. School of Economics & Management, Nanjing University of Science and Technology, Nanjing, 210094;　
    3. Institute for Science, Technology and Society, South China Normal University, Guangzhou, 510631;　
    4.School of Economics & Management, Beijing University of Technology, Beijing, 100124;　
    5.School of Information Management, Wuhan University, Wuhan, 430072;　
    6. Institute of Scientific and Technical Information of China, Beijing, 100038
  • Online:2024-03-26 Published:2024-04-11
  • About author:Zhou Haichen, research assistant, Ph.D., research interests include science and technology evaluation and text mining, Email: zhouhc@clas.ac.cn; Zhang Chengzhi, professor, Ph.D., research interests include information organization, information retrieval, data mining, and natural language processing; Hu Zhigang, professor, Ph.D., research interests include scientometrics and science of science; Xu Shuo, professor, Ph.D., research interests include scientometrics, science and technology intelligence analysis, and data mining; Mao Jin, associate professor, Ph.D., research interests include science and technology intelligence, big data analysis; Chen Liang, associate professor, Ph.D., research interests include data mining.
  • Supported by:
    This study is an outcome of the project "Extraction and Evaluation of Fine-grained Algorithmic Entity from Full-text Content of Academic Documents”(Grant No. 72074113) supported by National Natural Science Foundation of China

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Abstract: On September 14-16, 2023, the Sixth Chengdu Conference on Scientometrics & Evaluation was held, hosted by the National Science Library (Chengdu), Chinese Academy of Sciences and organized by the Sci-tech innovation Evaluation Research Center (SERC). The Fourth Academic Salon on Full-text Bibliometric analysis, initiated by Zhang Chengzhi and others, was an important event of the Chengdu Conference, receiving more than eighty experts and scholars' enthusiastic participation and in-depth communication. By combing and summarizing the speeches and discussions of the guests of the salon, this article summarizes the main contents of the salon into the aspects of large language model and full-text bibliometric analysis, the application scenario of full-text bibliometric analysis and so on, in order to reveal the research status and development trend of full-text bibliometric analysis.

Key words: Full-text bibliometrics, Large language model, Disruptive technology, Innovation identification

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