Identifying Important Topics and Knowledge Flow Paths with Topic-Citation Fusion
Liang Shuang1,2,Liu Xiaoping1,2(),Chai Wenyue1,2
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China 2Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
[Objective] Understanding and exploring the internal mechanism and direction of knowledge flow, this paper provides references for science and technology innovation, scientific evaluation, and decision-making. [Methods] We established a topic-based knowledge network and constructed the topic importance indicators with their impact factors and node intersection degrees. We used the maximum path search algorithm based on these important topics to construct the knowledge inflow and outflow paths. [Results] The new method could effectively identify the important topics. We also identified the knowledge flow paths and the domains with the most significant knowledge dissemination. [Limitations] The measurement of knowledge flow intensity between nodes needs to consider citation motivations and types. [Conclusions] This paper identifies two-way knowledge flows between topics. Topic groups communicate closely with each other within each discipline. Knowledge flow paths provide valuable references for grasping the research topic developments as a whole.
Spender J C. Making Knowledge the Basis of a Dynamic Theory of the Firm[J]. Strategic Management Journal, 1996, 17(S2): 45-62.
doi: 10.1002/smj.v17.2s
[2]
Drucker P F. Managing in a Time of Great Change[M]. Oxford: Butterworth Heinemann, 1995.
[3]
Nissen M E. Initiating a System for Visualizing and Measuring Dynamic Knowledge[J]. Technological Forecasting and Social Change, 2019, 140: 169-181.
doi: 10.1016/j.techfore.2018.04.008
[4]
Hagel III J, Brown J S, Davison L. Measuring the Forces of Long-Term Change: The 2009 Shift Index[EB/OL]. [2022-07-22]. https://www.johnseelybrown.com/shiftindex.pdf.
[5]
赵迪. 创新思维: 科学知识增长的灵魂[D]. 长春: 吉林大学, 2018.
[5]
(Zhao Di. Innovative Thinking: The Soul of Scientific Knowledge Increasing[D]. Changchun: Jilin University, 2018.)
[6]
Zhuge H. Discovery of Knowledge Flow in Science[J]. Communications of the ACM, 2006, 49(5): 101-107.
[7]
Garfield E, Sher I H, Torpie R J. The Use of Citation Data in Writing the History of Science[R]. Philadelphia: Institute for Scientific Information, 1964.
[8]
Hummon N P, Dereian P. Connectivity in a Citation Network: The Development of DNA Theory[J]. Social Networks, 1989, 11(1): 39-63.
doi: 10.1016/0378-8733(89)90017-8
[9]
刘懿, 周丽英. 主路径分析方法研究进展[J]. 数字图书馆论坛, 2019(10): 8-15.
[9]
(Liu Yi, Zhou Liying. Literature Review about Main Path Analysis Method[J]. Digital Library Forum, 2019(10): 8-15.)
[10]
Lucio-Arias D, Leydesdorff L. Main-Path Analysis and Path-Dependent Transitions in HistCiteTM-Based Historiograms[J]. Journal of the American Society for Information Science and Technology, 2008, 59(12): 1948-1962.
doi: 10.1002/asi.v59:12
(Ma Ruimin, Zhang Xin. Discovering the Knowledge Communication Main Path of a Domain Based on Pathfinder Algorithm[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(8): 856-863.)
(Liu Xiang, Ma Feicheng, Wang Xiaoguang. Formation and Process Model of Knowledge Networks[J]. Systems Engineering-Theory & Practice, 2013, 33(7): 1836-1844.)
doi: 10.12011/1000-6788(2013)7-1836
(He Jin, Guan Peng, Wang Yuefen. Construction and Evolution Analysis of Discipline Knowledge Network Based on Author-Topic Association[J]. Information Science, 2019, 37(1): 56-62, 67.)
(Wang Feifei, Wang Xiaohan, Xu Shuo, et al. Potential Knowledge Flow Detection from an Integrated Perspective of Three-Dimensional Citations: A Case Study of Gene Editing[J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(2): 184-193.)
(Shang Xianli. Research on Knowledge Dissemination in Cross-Disciplines Based on Topic Citation Network——An Example of Digital Library[J]. Information Science, 2018, 36(8): 53-59, 66.)
[18]
Yan E J. Finding Knowledge Paths Among Scientific Disciplines[J]. Journal of the Association for Information Science and Technology, 2014, 65(11): 2331-2347.
doi: 10.1002/asi.2014.65.issue-11
[19]
关鹏. 整合主题的学科知识网络建模与演化机理研究[D]. 南京: 南京理工大学, 2018.
[19]
(Guan Peng. Research on Modeling and Evolution Mechanism of Discipline Knowledge Network Based on Integrating Topic[D]. Nanjing: Nanjing University of Science and Technology, 2018.)
(Dong Kun, Xu Haiyun, Cui Bin. A Review of Knowledge Flow Research[J]. Journal of the China Society for Scientific and Technical Information, 2020, 39(10): 1120-1132.)
(Wang Yuefen, Wang Jinshu, Guan Peng. Research on Construction and Evolution Analysis of Discipline Knowledge Network Based on Topics Association[J]. Information Science, 2018, 36(9): 9-15, 102.)
[22]
Zhang G J, Liu L N, Wei F F. Key Nodes Mining in the Inventor-Author Knowledge Diffusion Network[J]. Scientometrics, 2019, 118(3): 721-735.
doi: 10.1007/s11192-019-03005-2
[23]
Zhao S X, Ye F Y. Exploring the Directed h-Degree in Directed Weighted Networks[J]. Journal of Informetrics, 2012, 6(4): 619-630.
doi: 10.1016/j.joi.2012.06.007
(Liu Chen, Zhang Qingpu, Shan Wei, et al. Construction and Analysis of Disciplinary Knowledge Flow Network[J]. Journal of the China Society for Scientific and Technical Information, 2009, 28(2): 257-265.)
(Bi Chongwu, Ye Guanghui, Peng Ze, et al. Network Analysis on Knowledge Flow in Citation Network from the Perspective of Citation Content[J]. Information Science, 2022, 40(2): 49-58.)
[26]
Sugiyama K, Kumar T, Kan M Y, et al. Identifying Citing Sentences in Research Papers Using Supervised Learning[C]// Proceedings of the 2010 International Conference on Information Retrieval & Knowledge Management. Piscataway: IEEE, 2010: 67-72.
(Xia Hongyu, Hu Qian, Wang Zhongyi. Tracing the Knowledge Flow Main Path Based on Important Citations[J]. Journal of the China Society for Scientific and Technical Information, 2022, 41(5): 451-462.)
[28]
Kim M, Baek I, Song M. Topic Diffusion Analysis of a Weighted Citation Network in Biomedical Literature[J]. Journal of the Association for Information Science and Technology, 2018, 69(2): 329-342.
doi: 10.1002/asi.2018.69.issue-2
[29]
Ma R M, Yan E J. Uncovering Inter-Specialty Knowledge Communication Using Author Citation Networks[J]. Scientometrics, 2016, 109(2): 839-854.
doi: 10.1007/s11192-016-2091-2
[30]
Yan E J. Research Dynamics, Impact, and Dissemination: A Topic-Level Analysis[J]. Journal of the Association for Information Science and Technology, 2015, 66(11): 2357-2372.
doi: 10.1002/asi.2015.66.issue-11
(Zhou Lixin, Liu Chen, Huo Liang'an, et al. Identification Algorithms of Center Node in Directed Complex Networks Based on Cross Degree[J]. Application Research of Computers, 2016, 33(11): 3299-3302, 3306.)
[32]
Mann G S, Mimno D, McCallum A. Bibliometric Impact Measures Leveraging Topic Analysis[C]// Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries. New York: ACM, 2006: 65-74.
(Jiang Lincheng. Research on Identifying Node and Edge Importance and Influence Maximization in Complex Networks[D]. Changsha: National University of Defense Technology, 2018.)
(Wang Pandi, Xiong Xiaojuan, Fu Ping, et al. Regulation of Synthetic Biology under Background of Implementing Biosafety Law[J]. Journal of Huazhong Agricultural University, 2021, 40(6): 231-245.)
