Title :
Research on Cooperative Relations for Identifying Abnormal Vertices in Complex Financial Networks
Author :
Guo Yanli ; Xue Yaowen
Author_Institution :
Sch. of Econ. & Manage., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Theory and application of complex network is one of the hot spots in many discipline now. In our economic life financial network is one kind of complex social network. This paper constructs two types of conception models of complex finance network which weights has special meaning. Firstly, this paper uses UCINET (a social network analysis software) to find the clustering characteristic of the finance network. Secondly, this paper constructs a financial network which its weights mean capital transfers frequency and uses short-path algorithm to find the correlation ship of any two account vertexes. All these can provide the foundation for further studies.
Keywords :
complex networks; financial data processing; graph theory; social networking (online); UCINET; capital transfer frequency; clustering characteristic; complex economic life financial network; cooperative relation; correlation ship; identifying abnormal vertices; short-path algorithm; social network analysis software; Banking; Computer crime; Electronic commerce; Electronic mail; Finance; Financial management; Frequency; Intelligent networks; Social network services; Technology management; complex network; financial network; social network analysis;
Conference_Titel :
Electronic Commerce and Business Intelligence, 2009. ECBI 2009. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3661-3
DOI :
10.1109/ECBI.2009.70