Abstract：To explore the evolution of inventor influence, this paper investigates the node influence model in a multi-layer graph sequential patent citation network. Divide network layers and construct the connections between layers based on the continuity of node influence and the attractiveness of high-influence nodes. After obtaining the time series evolution data of inventor influence, the distribution and evolution law of inventor influence is explored by using piecewise fitting method. An empirical analysis of patent data in the field of ‘Molecular Biology and Microbiology’ shows that the quality and quantity of patents determine the level of influence of inventors. With high-influence inventors continuing to receive attention, most medium-influence and low-influence inventors gradually are marginalized.
[1] BOMMARITO J, KATZ M, ZELNER L, et al. Distance measures for dynamic citation networks[J]. Physica A: Statistical Mechanics and Its Applications,2010,389(19): 42014208. [2] 关鹏,王曰芬,傅柱,等.专利合作网络小世界特性对企业技术创新绩效的影响研究[J].图书情报工作,2021,65(18):105116. GUAN P, WANG Y F, FU Z, et al. Research on the impact of small-world characteristics of patent cooperation network on enterprise technological innovation performance[J]. Library and Information Service,2021,65(18):105116. [3] 方锦清.多层超网络探索中的若干问题与思考[J].科技导报,2017(14):3643. FANG J Q. Some problems and thinking on the exploration of multilayer super network[J]. Science & Technology Review,2017(14):3643. [4] MORONE F, DEL F G, MAKSE H A. The k-core as a predictor of structural collapse in mutualistic ecosystems[J]. Nature Physics,2019,15(1):95102. [5] MORONE F, MAKSE H A. Corrigendum: influence maximization in complex networks through optimal percolation[J]. Nature,2015,527(7579):544544. [6] MUSMECI N, NICOSIA V, ASTE T, et al. The multiplex dependency structure of financial markets[J]. Complexity,2017(2):113. [7] 先兴平,吴涛.大数据时代网络科学研究进展——多层复杂网络理论[J].产业与科技论坛,2016,15(19):8081. XIAN X P, WU T. Research progress in network science in the era of big data—multilayer complex network theory[J]. Industrial & Science Tribune,2016,15(19):8081. [8] 徐凤,朱金福,杨文东.高铁民航复合网络的构建及网络拓扑特性分析[J].复杂系统与复杂性科学,2013,10(3):111. XU F, ZHU J F, YANG W D. Construction of high-speed railway and airline compound network and the analysis of its network topology characteristics[J]. Complex Systems and Complexity Science,2013,10(3):111. [9] 郑春园.多重网络中疾病与意识传播的相互作用[D].天津:天津理工大学, 2018. ZHENG C Y. Interplay between disease and awareness spreading on multiplex networks[D]. Tianjin:Tianjin University of Technology,2018. [10] 杨剑楠,刘建国,郭强.基于层间相似性的时序网络节点重要性研究[J].物理学报,2018, 67(4):279286. YANG J N, LIU J G, GUO Q.Node importance idenfication for temporal network based on interlayer similarity[J]. Acta Physica Sinica,2018, 67(4):279286. [11] 郭强,殷冉冉,刘建国.基于TOPSIS的时序网络节点重要性研究[J].电子科技大学学报,2019,48(2):296300. GUO Q, QIN R R, LIU J G.Node Importance identification for temporal networks via the TOPSIS method[J]. Journal of University of Electronic Science and Technology of China,2019,48(2):296300. [12] 张欣.多层复杂网络理论研究进展:概念、理论和数据[J].复杂系统与复杂性科学,2015, 12(2):103107. ZHANG X. Multilayer network science: concepts, theories and data[J]. Complex Systems and Complexity Science,2015, 12(2):103107. [13] MANASKASEMSAK B , RUNGSAWANG A , YAMANA H. Timeweighted web authoritative ranking[J]. Information Retrieval, 2011, 14(2):133157. [14] CHEN S H, YAN H, Li J C, et al. Improvement of pagerank algorithm: an authoritative and temporal based approach[C] //IEEE International Conference on ComputerAided Industrial Design & Conceptual Design. San Jose, CA: IEEE,2014:14. [15] HU W S, ZOU H T, GONG Z G. Temporal PageRank on social networks[C] // International Conference on Web Information Systems Engineering. FL,USA: Springer,2015:62276. [16] PASTOR S R, CASTELLANO C, MIEGHEM P V, et al. Epidemic processes in complex networks[J]. Reviews of Modern Physics,2015,87(3):925979. [17] ROZENSHTEIN P, GIONIS A. Temporal PageRank[C] // European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Riva del Garda, Italy :Springer, 2016:674689. [18] ROCHA L, MASUDA N. Random walk centrality for temporal networks[J]. New Journal of Physics,2014,16(6):063023. [19] 牌艳欣,李长玲,徐璐.弱引文关系视角下跨学科相关知识组合识别方法探讨——以情报学为例[J].图书情报工作,2020,64(21),111119. PAI Y X, LI C L, XU L. Discussion on the method of interdisciplinary related knowledge combination identification on the perspective of weak citation relationship—taking information science for example[J]. Library and Information Service,2020,64(21),111119. [20] 王玙,刘东苏.基于PageRank的动态网络核心节点检测及演化分析[J].情报学报,2018, 37(7):703711. WANG Y, LIU D S. Vital node detection and evolution analysis in dynamic networks based on pageRank[J]. Journal of the China Society for Scientific and Technical Information,2018, 37(7):703711. [21] 迟阔.基于节点间吸引力的动态社会网络社区演化和链接预测的研究[D].哈尔滨:哈尔滨工程大学,2019. CHI K. Research on Community evolution and link prediction in dynamic social networks based on the attraction force between nodes[D]. Harbin:Harbin Engineering University,2019. [22] 崔林蔚,陆颖.基于作者署名排序的作者贡献要素分析——以《图书情报工作》20152016年作者贡献声明为例[J].图书情报工作,2017,61(9):8086. CUI L W, LU Y. Analysis of author contribution factors based on article author order—taking library and information service as an example[J]. Library and Information Service,2017,61(9):8086.
