The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks

The researchs on the structure and formation mechanism of social networks lead to several models with differences in the attachment patterns of new links (edges). In fact, the driving factor behind the addition of new links is just as important as the attachment patterns, while very little attention...

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Main Authors: Zhijing Xu, Zhenghu Zu, Tao Zheng, Wendou Zhang, Qing Xu
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/906785
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spelling doaj-8c59c20c9deb4f89b737394d99bda4222020-11-24T22:32:27ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/906785906785The Effects of Decision-Making Processes and Population Turnover on the Formation of Social NetworksZhijing Xu0Zhenghu Zu1Tao Zheng2Wendou Zhang3Qing Xu4Beijing Institute of Biotechnology, 20 East Avenue, Fengtai District, Beijing 100071, ChinaBeijing Institute of Biotechnology, 20 East Avenue, Fengtai District, Beijing 100071, ChinaBeijing Institute of Biotechnology, 20 East Avenue, Fengtai District, Beijing 100071, ChinaBeijing Institute of Biotechnology, 20 East Avenue, Fengtai District, Beijing 100071, ChinaBeijing Institute of Biotechnology, 20 East Avenue, Fengtai District, Beijing 100071, ChinaThe researchs on the structure and formation mechanism of social networks lead to several models with differences in the attachment patterns of new links (edges). In fact, the driving factor behind the addition of new links is just as important as the attachment patterns, while very little attention has been devoted so far to this exploration. We present an agent-based model which could successfully reproduce large-scale social networks. We find that the structure of social networks is a consequence of continuous individuals’ decision-making processes based on self-evaluations and the turnover of the population. The individuals’ self-evaluation processes are key motivating factors for the addition of new links, while the attachment patterns and the turnover of the population should be responsible for the topology of social networks. The resulting networks of our model display dynamics between order and randomness, which is greatly consistent with current observations and research achievements of social networks. We also find that some plausible properties of empirical data are actually artifacts due to the boundedness of sampling. Our research has revealed the driving factors behind the evolution of social networks as well as the underlying evolving patterns. These findings will lead to a better understanding of social structures.http://dx.doi.org/10.1155/2013/906785
collection DOAJ
language English
format Article
sources DOAJ
author Zhijing Xu
Zhenghu Zu
Tao Zheng
Wendou Zhang
Qing Xu
spellingShingle Zhijing Xu
Zhenghu Zu
Tao Zheng
Wendou Zhang
Qing Xu
The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
Mathematical Problems in Engineering
author_facet Zhijing Xu
Zhenghu Zu
Tao Zheng
Wendou Zhang
Qing Xu
author_sort Zhijing Xu
title The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
title_short The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
title_full The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
title_fullStr The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
title_full_unstemmed The Effects of Decision-Making Processes and Population Turnover on the Formation of Social Networks
title_sort effects of decision-making processes and population turnover on the formation of social networks
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description The researchs on the structure and formation mechanism of social networks lead to several models with differences in the attachment patterns of new links (edges). In fact, the driving factor behind the addition of new links is just as important as the attachment patterns, while very little attention has been devoted so far to this exploration. We present an agent-based model which could successfully reproduce large-scale social networks. We find that the structure of social networks is a consequence of continuous individuals’ decision-making processes based on self-evaluations and the turnover of the population. The individuals’ self-evaluation processes are key motivating factors for the addition of new links, while the attachment patterns and the turnover of the population should be responsible for the topology of social networks. The resulting networks of our model display dynamics between order and randomness, which is greatly consistent with current observations and research achievements of social networks. We also find that some plausible properties of empirical data are actually artifacts due to the boundedness of sampling. Our research has revealed the driving factors behind the evolution of social networks as well as the underlying evolving patterns. These findings will lead to a better understanding of social structures.
url http://dx.doi.org/10.1155/2013/906785
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