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Data Analysis and Knowledge Discovery  2024, Vol. 8 Issue (2): 99-113    DOI: 10.11925/infotech.2096-3467.2022.1335
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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
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Abstract  

[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.
Key words： Citation Analysis      Topic Citation Network      Topic Importance      Knowledge Flow      Path Analysis     
Received: 16 December 2022      Published: 28 April 2023
ZTFLH:  G353  
Fund:Project of Literature and Information Capacity Building, Chinese Academy of Sciences(E1290423)
Corresponding Authors: Liu Xiaoping，ORCID：0000-0002-3342-8041，E-mail：liuxp@mail.las.ac.cn。   
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Shuang Liang
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Cite this article:

Liang Shuang, Liu Xiaoping, Chai Wenyue. Identifying Important Topics and Knowledge Flow Paths with Topic-Citation Fusion. Data Analysis and Knowledge Discovery, 2024, 8(2): 99-113.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2022.1335     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2024/V8/I2/99

Research Design and Methodology
Construction Process of Topic Reference Network
Knowledge Flow Path Construction Method （Taking Knowledge Outflow as an Example）
Topic Reference Network of Synthetic Biology Field
主题节点 入度 出度 节点交叉度
genome engineering 53 53 53.00
assembly engineering 51 48 49.48
metabolic engineering 47 48 47.50
gene regulation 48 43 45.43
gene expression 48 43 45.43
gene circuit 49 42 45.37
mathematical simulation and
functional testing		 42 36 38.89
gene mutation 43 35 38.80
DNA sequence analysis 48 30 37.97
cell engineering 41 34 37.34
Node Crossover Degree in Topic Network （Partial）
主题 2002年 2003年 2004年 … 2019年 2020年 2021年
gene mutation 11/118 9/138 7/63 … 58/321 60/269 56/282
assembly engineering 4/5 1/3 4/28 … 212/1714 246/1786 240/1842
genome engineering 3/10 4/35 3/56 … 322/1940 380/2743 424/3280
metabolic engineering 0/0 0/0 1/0 … 393/2810 437/3477 453/3834
gene circuit 0/0 0/0 0/0 … 60/374 78/418 77/505
cell engineering 0/0 0/0 2/5 … 67/605 71/464 72/437
cluster 0/0 0/0 0/0 … 0/0 0/0 1/12
gene regulation 9/33 8/31 9/22 … 114/533 115/619 108/622
cancer treatment 37/252 52/215 62/328 … 125/745 151/1046 161/1546
biosensor 1/0 0/0 0/0 … 18/264 27/257 30/220
The Number of Literatures on the Topic in Different Years and the Corresponding Citation Frequency （Partial）
主题 2002年 2003年 2004年 … 2019年 2020年 2021年 平均影响因子
gene mutation 10.73 15.33 9.00 … 5.53 4.48 5.04 7.52
assembly engineering 1.25 3.00 7.00 … 8.08 7.26 7.68 7.34
genome engineering 3.33 8.75 18.67 … 6.02 7.22 7.74 6.47
metabolic engineering 0 0 0 … 7.15 7.96 8.46 6.31
gene circuit 0 0 0 … 6.23 5.36 6.56 6.24
cell engineering 0 0 2.50 … 9.03 6.54 6.07 6.06
cluster 0 0 0 … 0 0 12.00 6.05
gene regulation 3.67 3.88 2.44 … 4.68 5.38 5.76 5.98
cancer treatment 6.81 4.13 5.29 … 5.96 6.93 9.60 5.92
biosensor 0 0 0 … 14.67 9.52 7.33 5.64
Impact Factors and Average Values of Topics in Different Years （Partial）
主题节点 交叉度 k 平均影响因子 T I F ˉ 重要度值 I
assembly engineering 49.48 7.34 363.18
genome engineering 53.00 6.47 342.91
metabolic engineering 47.50 6.31 299.73
gene mutation 38.80 7.52 291.78
gene circuit 45.37 6.24 283.11
gene regulation 45.43 5.98 271.67
cell engineering 37.34 6.06 226.28
cancer treatment 36.47 5.92 215.90
DNA sequence analysis 37.97 4.88 185.29
biosensor 28.50 5.64 160.74
Importance Value of Topic Node （Partial）
The Change of Network Efficiency Decline Ratio and Maximum Connectivity Coefficient with Respect to the Number of Nodes Removed
知识流入视角（作为施引主题） 知识流出视角（作为被引主题）
被引主题 引用次数 流入比例 施引主题 引用次数 流出比例
cell engineering 7 0.03 cell engineering 3 0.01
molecular biology 2 0.01 molecular biology 3 0.01
assembly engineering 40 0.17 assembly engineering 40 0.20
gene circuit 28 0.12 gene circuit 25 0.12
biosensor 2 0.01 biosensor 2 0.01
metabolic engineering 14 0.06 metabolic engineering 15 0.07
cancer treatment 2 0.01 cancer treatment 2 0.01
DNA sequence analysis 10 0.04 DNA sequence analysis 10 0.05
mathematical simulation and functional testing 14 0.06 mathematical simulation and functional testing 15 0.07
gene mutation 10 0.04 gene mutation 2 0.01
network biology 5 0.02 enzyme catalysis 4 0.02
gene regulation 52 0.23 gene regulation 18 0.09
gene expression 9 0.04 gene expression 7 0.03
genome engineering 31 0.14 genome engineering 49 0.24
The Proportion of Knowledge Flow Between Topics from the Perspective of Knowledge Inflow and Outflow
Path Construction from the Perspective of Knowledge Inflow
Path Construction from the Perspective of Knowledge Outflow
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