Library and Information Service >
Research on the Dynamic Evolution of Domain Knowledge Based on the Network Centrality
Received date: 2016-05-16
Revised date: 2016-06-25
Online published: 2016-07-20
[Purpose/significance] The dynamic analysis of the centrality in knowledge networks can reveal the laws and models of the domain knowledge development. The detection has important significance for the insight into the derived, cross and fusion phenomena in the process of knowledge development.[Method/process] This study used the centrality analysis technology of the complex network analysis as the main research method and structured domain knowledge networks based on co-occurrence relations of domain keywords. The knowledge development process in specific domains was dynamically tracked and analyzed via time series with core-emergence, bridging-control, and relevance-closeness.[Result/conclusion] The results show that the growth rate of knowledge relationships is much higher than the literature and keywords growths; the core-emergence degree of domain knowledge shows a fluctuation growth state; the bridging-control degree between domain knowledge has an upward trend over time; the relevance-closeness degree among domain knowledge gradually lowers along the timeline. These rules of the knowledge evolution help to grasp the venation of the domain knowledge evolution, and play a positive role in revealing knowledge development models and rules.
Key words： domain knowledge; complex network; network centrality; time series
Teng Guangqing, He Defang, Peng Jie, Zhao Runan, Zhang Libiao . Research on the Dynamic Evolution of Domain Knowledge Based on the Network Centrality[J]. Library and Information Service, 2016 , 60(14) : 128 -134,141 . DOI: 10.13266/j.issn.0252-3116.2016.14.016
[1] 波普尔. 客观的知识——一个进化论的研究[M]. 舒炜光, 卓如飞, 梁咏新, 等译. 杭州:中国美术学院出版社, 2003:258-283.
[2] BELKIN N J, ROBERTSON S E. Information science and the phenomenon of information[J]. Journal of the American Society for Information Science, 1976, 27(4):197-204.
[3] STROGATZ S H, WATTS D J. Collective dynamics of ‘small world’ networks[J]. Nature, 1998, 393(6684):440-442.
[4] BARABASI A L, ALBERT R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439):509-512.
[5] LEWIS T G. 网络科学:原理与应用[M]. 陈向阳, 巨修炼, 等译. 北京:机械工业出版社, 2011:87-140.
[6] HU C, RACHERLA P. Visual representation of knowledge networks:a social network analysis of hospitality research domain[J]. International journal of hospitality management, 2008, 27(2):302-312.
[7] POLITES G L, WATSON R T. Using social network analysis to analyze relationships among IS journals[J]. Journal of the Association for Information Systems, 2009, 10(8):595-636.
[8] COSCIA M, GIANNOTTI F, PENSA R. Social network analysis as knowledge discovery process:a case study on digital bibliography[C]//Proceedings of the 2009 international conference on advances in social network analysis and mining. Washington:IEEE Computer Society, 2009:279-283.
[9] KRAFFT J, QUATRARO F, SAVIOTTI P P. The knowledge base evolution in biotechnology:a social network analysis[J]. Economics of innovation and new technology, 2011, 20(5):445-475.
[10] PHAM M C, KLAMMA R, JARKE M. Development of computer science disciplines:a social network analysis approach[J].Social network analysis and mining, 2011, 1(4):321-340.
[11] 邱均平, 王菲菲. 基于SNA的国内竞争情报领域作者合作关系研究[J]. 图书馆论坛, 2010, 30(6):34-40, 134.
[12] 陈远, 王菲菲. 基于CSSCI的国内情报学领域作者文献耦合分析[J]. 情报资料工作, 2011(5):6-12.
[13] 邱均平, 王菲菲. 基于引证关系的国内情报学领域作者研究活力与影响力分析[J]. 图书馆论坛, 2011, 31(6):51-61.
[14] 李纲, 李春雅, 李翔. 基于社会网络分析的科研团队发现研究[J]. 图书情报工作, 2014, 58(7):63-70, 82.
[15] VIERMETZ M, SKUBACZ M. Using topic discovery to segment large communication graphs for social network analysis[C]//Proceedings of the IEEE/WIC/ACM international conference on web intelligence. Silicon Valley:IEEE computer society, 2007:95-99.
[16] YANG J, SHEN Q, HO M. An overview of previous studies in stakeholder management and its implications for the construction industry[J]. Journal of facilities management, 2009, 7(2):159-175.
[17] SCHULTZ-JONES B. Examining information behavior through social networks:an interdisciplinary review[J]. Journal of documentation, 2009, 65(4):592-631.
[18] 赵蓉英, 王菊. 图书馆学知识图谱分析[J]. 中国图书馆学报, 2011, 37(3):40-50.
[19] 张玥, 朱庆华. Web 2.0环境下学术交流的社会网络分析:以博客为例[J]. 情报理论与实践, 2009, 32(8):28-32.
[20] 刘则渊, 尹丽春. 国际科学学主题共词网络的可视化研究[J]. 情报学报, 2006, 25(5):634-640.
[21] 滕广青, 毕强. 知识组织体系的演进路径及相关研究的发展趋势探析[J]. 中国图书馆学报, 2010, 36(5):49-53.
[22] MIZRUCHI M S. Social network analysis:recent achievements and current controversies[J]. Acta sociologica, 1994, 37(4):329-343.
[23] 格雷克. 信息简史[M]. 高博, 译. 北京:人民邮电出版社, 2013:409-421.
[24] FREEMAN L C. Centrality in social networks conceptual clarification[J]. Social networks, 1979, 1(3):215-239.
/
| 〈 |
|
〉 |
