Evolutionary Analysis on Information Sharing Behavior in Social Networks Based on Social Evolutionary Game

YU Jian-ye; WANG Yuan-zhuo; JIN Xiao-long; CHENG Xue-qi

doi:10.3969/j.issn.0372-2112.2018.01.031

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Evolutionary Analysis on Information Sharing Behavior in Social Networks Based on Social Evolutionary Game

更新时间：2025-07-16

- Evolutionary Analysis on Information Sharing Behavior in Social Networks Based on Social Evolutionary Game
- Acta Electronica Sinica Vol. 46, Issue 1, Pages: 223-229(2018)
- 作者机构：
  
  1. 中国科学院计算技术研究所, 中国科学院网络数据科学与技术重点实验室,北京,100190
  2. 北京物资学院,北京,101149
  3. 中国科学院计算技术研究所中国科学院网络数据科学与技术重点实验室,北京,100190
  4. 北京物资学院,北京,101149
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2018.01.031
  CLC： TN911
- Published Online：25 January 2018，
  
  Published：2018
- 稿件说明：
移动端阅览
YU Jian-ye, WANG Yuan-zhuo, JIN Xiao-long, et al. Evolutionary Analysis on Information Sharing Behavior in Social Networks Based on Social Evolutionary Game[J]. Acta Electronica Sinica, 2018, 46(1): 223-229.
DOI：

YU Jian-ye, WANG Yuan-zhuo, JIN Xiao-long, et al. Evolutionary Analysis on Information Sharing Behavior in Social Networks Based on Social Evolutionary Game[J]. Acta Electronica Sinica, 2018, 46(1): 223-229. DOI： 10.3969/j.issn.0372-2112.2018.01.031.

摘要

本文基于社交演化博弈模型研究了社交网络中用户信息分享行为的合作演化.在社交演化博弈模型中，用户通过不断地模仿他关注的最成功的用户的行为策略来改进自身的短期效用，或者根据声誉调整他关注的用户来改善自身所处的声誉环境，进而改进自身的长期声誉，而用户间信息分享所构成的群体交互则使用公共品博弈进行建模.通过对社交演化博弈模型的数值仿真，揭示了用户间关注关系更新的频率、用户对声誉的追逐程度和群体放大效应在社交网络演化中的影响.同时，本文也应用了社交演化博弈模型对新浪微博进行了分析，加深了人们对社交网络中信息分享行为的合作演化的理解.

Abstract

In order to understand the evolutionary mechanisms on social networks

we investigate the evolution of information sharing behavior on directed and dynamic social networks using social evolutionary games

in which agents aim to improve their short-term utility and long-term reputation by imitating the most successful strategy from their partners and adjusting their partnerships

respectively. The public goods game is used as a metaphor for the interactions of agents on social networks. The results of numerical simulations reveal the effects of the frequency of partner adjusting

reputation pursuit and group effects on the evolution of social networks. Finally

an application of social evolutionary games on SinaWeibo is conducted

which may help us understand the mechanism behind the evolution of social networks.

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