A New Analysis Method for Simulations Using Node Categorizations

Author

Yuasa, Tomoyuki ; Shirayama, Susumu

Author_Institution

Sch. of Eng., Univ. of Tokyo, Tokyo, Japan

fYear

2011

fDate

25-27 July 2011

Firstpage

305

Lastpage

312

Abstract

Most research concerning the influence of network structure on phenomena taking place on the network focus on relationships between global statistics of the network structure and characteristic properties of those phenomena, even though local structure has a significant effect on the dynamics of some phenomena. In the present paper, we propose a new analysis method for phenomena on networks based on a categorization of nodes. First, local statistics such as the average path length and the clustering coefficient for a node are calculated and assigned to the respective node. Then, the nodes are categorized using the self-organizing map (SOM) algorithm. Characteristic properties of the phenomena of interest are visualized for each category of nodes. The validity of our method is demonstrated using the results of two simulation models.

Keywords

category theory; complex networks; network theory (graphs); self-organising feature maps; statistical analysis; average path length; clustering coefficient; global statistics; local statistics; network structure influence; node categorization; self organizing map algorithm; Analytical models; Communities; Heating; Layout; Mathematical model; Simulation; Visualization; Complex Network; Data Mining; Multi-Agent Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on

Conference_Location

Kaohsiung

Print_ISBN

978-1-61284-758-0

Electronic_ISBN

978-0-7695-4375-8

Type

conf

DOI

10.1109/ASONAM.2011.40

Filename

5992593