Graph-theoretic node importance mining in world city networks: methods and applications
| Date | 15 May 2017 |
| Pages | 57-65 |
| DOI | https://doi.org/10.1108/IDD-09-2016-0032 |
| Published date | 15 May 2017 |
| Author | Shan Xue,Li Xiong,Zhao Lu,Jia Wu |
| Subject Matter | Library & information science,Library & information services,Lending,Document delivery,Collection building & management,Stock revision,Consortia |
Graph-theoretic node importance mining in
world city networks: methods and
applications
Shan Xue
Shanghai University, Shanghai, China and University of Technology Sydney, Sydney, Australia
Li Xiong and Zhao Lu
School of Management, Shanghai University, Shanghai, China, and
Jia Wu
University of Technology Sydney, Sydney, Australia
Abstract
Purpose – This study aims to review the literature on graph-theoretic mining methods for node importance in both static and dynamic world city
networks, which is correspondingly categorised by graph-theoretic node importance mining on network topologies and transmission mechanisms.
Design/methodology/approach – The authors overview the graph-theoretic indicators of node importance: centrality and power. Then, the
methods of graph-theoretic node importance mining on network topologies are assessed with node relevance, centrality- and power-based
measurements, heterogeneous fusion and other miscellaneous approaches. The latest progress in transmission mechanisms is also reviewed in this
study involving network evolution, node immunisation and robustness in dynamics. Finally, the findings are analysed and future directions in this
field are suggested.
Findings – The method development of node importance mining is driven by complex application-based problems within a transmission mechanism.
Fusion measurements, based on centrality and power, are extended by other graph mining techniques in which power has a significant role. In
conclusion, the trends of node importance mining focus on power-embedded fusion measurements in the transmission mechanism-based complex
applications.
Originality/value – This is the first systematic literature review of node importance from the view of graph-theoretic mining.
Keywords Business intelligence, Complex network, Graph mining, Node importance, Resource distribution, World city network
Paper type Literature review
Introduction
Traditional world city networks (WCNs) use graph theory to
express nodes and links in perspective of complex networks
(Frideman, 1986). The cities in WCN models are denoted as
a set of nodes in networks, and the flow of resources between
cities is denoted as a set of links. In this way, a WCN can be
extracted as a complex network model and mapped into an
adjacent matrix. In this paper, we survey the articles that use
complex network theories to extract WCNs as a complex
system and use graph-theoretic node importance mining
methods (Figure 1).
In the real world, the rapid development of global finance
and technology has led to the inclusion of a new set of cities in
WCNs. The emergence of developing cities and these changes
to the WCN have attracted attention from both academics and
business. Evaluating the importance of nodes in a WCN is a
fundamental academic question, but it is also very challenging
to detect these changes. One of the phenomena within these
network changes is that developing cities are replacing the
positions of other cities that used to be important in the world.
The significance and innovations of graph-theoretic node
importance mining in WCNs are as follows:
●it represents real-world networks as a part of WCN, for
example, in document networks, financial networks and
cultural networks;
●it prevents the negative influence of WCNs, for example,
controlling and preventing the spread of disease over
WCNs; and
●it improves the robustness of WCNs by network
optimisation.
WCNs combine two concepts: cities and complex systems.
Previous research has defined node importance, and how to
evaluate the importance of nodes within a WCN has also been
discussed. Within the three perspectives of node importance
mining – social network analysis, system science and
information searching – Neal (2011) made great contributions
to node importance mining in WCNs by proposing a
The current issue and full text archive of this journal is available on
Emerald Insight at: www.emeraldinsight.com/2398-6247.htm
Information Discovery and Delivery
45/2 (2017) 57–65
© Emerald Publishing Limited [ISSN 2398-6247]
[DOI 10.1108/IDD-09-2016-0032]
Received 23 September 2016
Revised 20 November 2016
6 December 2016
Accepted 19 December 2016
57
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