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  • 标题:Memory Limited Trust Public Opinion Evolution Model In Accelerated Growth HK Network
  • 本地全文:下载
  • 作者:Zhang Jingshan ; Ma Baohua ; Sun Shibao
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2017
  • 卷号:14
  • 期号:1
  • 出版社:IJCSI Press
  • 摘要:To research the influence of individual subjectivity for opinion evolution, improved classical bounded confidence model, introduced firmness degree, trust degree and memory length, proposed a new method for measuring the influence among individuals. In consideration of the accelerated growth characteristics of real networks, established a network public opinion evolution model with memory mechanism based on accelerated growth HK network; studied the influence of trust threshold and memory length on public opinion evolution. The results show that, the value of trust threshold is inversely proportional to the final number of opinion clusters; memory length is proportional to the time of group opinions convergence.
  • 关键词:Network opinion; Accelerated growth; Memory; limitary
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