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Selforganizology, 2016, 3(3): 75-86
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Article

Screening node attributes that significantly influence node centrality in the network

WenJun Zhang
School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; International Academy of Ecology and Environmental Sciences, Hong Kong

Received 19 December 2015;Accepted 16 January 2016;Published online 1 September 2016
IAEES

Abstract
In present study, I proposed a method to screen node attributes that significantly influencing node centrality in the network. One of four node centralities, degree centrality, closeness centrality, betweenness centrality, and circuit centrality, can be used as the dependent variable and attribute-by-node data are used as the data of independent variables. Stepwise linear regression method was applied to screen statistically significant node attributes from candidate attributes. Matlab codes of the algorithm are provided also.

Keywords network;node attributes;node centrality;attribute screening;stepwise linear regression.

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