Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/83969
Type: | Conference paper |
Title: | A practical simulation method for social networks |
Author: | Zeng, R. Sheng, Q. Yao, L. Xu, T. Xie, D. |
Citation: | AWC 13 Proceedings of the First Australasian Web Conference - volume 144, 2013/ H. Ashman, Q. Z. Sheng, A. Trotman (eds.): pp.27-34 |
Publisher: | Australian Computer Society, Inc |
Publisher Place: | Online |
Issue Date: | 2013 |
ISBN: | 9781921770296 |
Conference Name: | Australasian Web Conference (2013 : Adelaide, South Australia) |
Statement of Responsibility: | Rui Zeng, Quan Z. Sheng, Lina Yao,Tianwei Xu,Dong Xie |
Abstract: | With the increasing popularity of social networks, it is becoming more and more crucial for the decision makers to analyze and understand the evolution of these networks in order to identify e.g., potential business opportunities. Unfortunately, understanding social networks, which are typically complex and dynamic, is not an easy task. In this paper, we propose an effective and practical approach for simulating social networks. We first develop a social network model that considers the addition and deletion of nodes and edges. We consider the nodes' in-degree, inter-nodes' close degree, which indicates how close the nodes are in the social network, and the limit of the network size in the social network model. We then develop a graph-based stratified random sampling algorithm for generating an initial network. To obtain the snapshots of a social network of the past, current and the future, we further develop a close degree algorithm and a close degree of estimation algorithm. The degree distribution of our model follows a power-law distribution with a "fat-tail". Experimental results using real-life social networks show the effectiveness of our proposed simulation method. |
Keywords: | Social network simulation adjacent matrix power–law distribution in-degree close degree |
Rights: | Copyright © 2012, Australian Computer Society |
Description (link): | http://cs.adelaide.edu.au/~awc2013/index.html |
Published version: | http://dl.acm.org/citation.cfm?id=2527212&CFID=387481507&CFTOKEN=18444863 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.