[Purpose/significance] This paper used the published authors of Wuhan University and Nanjing University in the field of library and information research and their number of submissions as research objects to identify the structural characteristics and differences of the intranet's internal cooperation network. It can provide reference for the cooperation and communication among authors, and promote better development in this field.[Method/process] Firstly, this paper created cooperative network between the first author and the other author, and count up the cooperation between Wuhan University and Nanjing University. Then, it visualized the cooperative network relationship though Pajek (a social network analysis software), while did the triad census analysis of characteristics. [Result/conclusion] The analysis shows that Wuhan University prefer to publish papers through two personal cooperation. Sub-authors often cooperate with high-yield authors, the network tends to converge, and lack of cooperation among sub-authors; Nanjing University scholars prefer to publish papers independently as the first author, more authors join cooperation network as the first author so that the network expands outward. Meanwhile, there's less cooperation among different first authors.
Wang Jiaxin
,
Hou Haiyan
,
Huang Fu
,
Hu Zhigang
. Triad Census Analysis on Structural Characteristics and Differences of Cooperative Network[J]. Library and Information Service, 2018
, 62(9)
: 102
-111
.
DOI: 10.13266/j.issn.0252-3116.2018.09.013
[1] WOLFGAN G,CHRISTO D L. Modelling and measuring multilateral co-authorship in international scientific collaboration. Part Ⅱ. A comparative study on the extent and change of international scientific collaboration links[J]. Scientometrics,1997,40(3):605-626.
[2] EILEEN O, RONALD R. Social network analysis:a powerful strategy, also for the information sciences[J]. Journal of information science, 2002,28(6):441-453.
[3] 邱均平,董克.作者共现网络的科学研究结构揭示能力比较研究[J].中国图书馆学报,2014,40(1):15-24.
[4] 侯剑华,王仲禹. 大科学项目的国际科学合作模式及特点探究——以斯隆数字巡天(SDSS)项目为例[J]. 现代情报,2016,36(12):126-132.
[5] BATAGELJ V,MRVAR A. A subquadratic triad census algorithm for large sparse networks with small maximum degree[J]. Social networks,2001,23(3):237-243.
[6] CHU S H, CHENG J. Triangle listing in massive networks[J].ACM transactions on knowledge discovery from data,2012,6(4):1-17,32.
[7] DEREK D, HUDA A, SWAPNA S G. Triads, transitivity, and social effects in user interactions on Facebook[C]//International conference on computational aspects of social networks. New York:IEEE, 2013:68-73.
[8] HUDA A, SWAPNA S G. Mining social capital on online social networks with strong and weak ties[C]//AWAN I, YOUNAS M. Proceedings 20162nd international conference on open and big data. Los Alamitos:IEEE Computer Soc, 2016:9-16.
[9] 傅春花. 合作网络及合作竞争网络的相关研究[D]. 扬州:扬州大学,2009.
[10] 董克,刘德洪,江洪. 基于三方关系组的引用网络结构分析[J]. 情报理论与实践,2010,33(11):50-53.
[11] 郑笑寒. 论知识产权理论的哲学反思——以创新收益为视角[D]. 南昌:南昌大学,2007.
[12] HOLLAND P W, LEINHARDT S. An exponential family of probability-distributions for Directed-Graphs[J]. Journal of the American Statistical Association, 1981, 76(373):33-50.
