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New Technology of Library and Information Service  2014, Vol. 30 Issue (7): 84-91    DOI: 10.11925/infotech.1003-3513.2014.07.12
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Research on the Structural Features of Keyword Network of Scientific Research Areas:An Empirical Study of LIS
Chen Guo, Hu Changping
Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
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[Objective] This paper aims to reveal the common structural features of keyword network of scientific research areas both at the macro level and micro level.[Methods] Three keyword networks are constructed. Theirmacro feature properties are compared with ER network, BA network and SW network, and regression analysis on theirmicro feature properties are performed.[Results] The degree sequence of keyword network shows a power-law distribution, the average clustering coefficient of them is extremely high and the average path length of them is short.The degree, betweenness centrality, eigenvector centrality, and triad closure of nodes and the frequency of keywords have positive linear correlations, while there is an inverse relationship between the local clustering coefficient of nodesand their degree.[Limitations] Samples need to be expanded to more other disciplines.[Conclusions] The keyword network of scientific research areas are special scale-free networks with small world effect, modularity, hierarchy and high centripetalism.

Key wordsKeyword network      Co-word network      Network structure      Digital library      Information service      Knowledge management     
Received: 21 March 2014      Published: 20 October 2014
:  G250.7  

Cite this article:

Chen Guo, Hu Changping. Research on the Structural Features of Keyword Network of Scientific Research Areas:An Empirical Study of LIS. New Technology of Library and Information Service, 2014, 30(7): 84-91.

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