• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 论文 • 上一篇    下一篇

语言竞争社会仿真模型与计算实验

曾振华1,毕贵红2,张寿明1,蔡子龙2   

  1. (1.昆明理工大学信息工程与自动化学院,云南 昆明 650500;2.昆明理工大学电力工程学院,云南 昆明 650500)
  • 收稿日期:2015-06-29 修回日期:2015-10-25 出版日期:2016-12-25 发布日期:2016-12-25
  • 基金资助:

    国家自然科学基金(61364022)

A social simulation model of language competition
and its computation experiments

ZENG Zhenhua1,BI Guihong2,ZHANG Shouming1,CAI Zilong2   

  1. (1.Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500;
    2.Faculty of Electric Power Engineering,Kunming University of Science and Technology,Kunming 650500,China)
     
  • Received:2015-06-29 Revised:2015-10-25 Online:2016-12-25 Published:2016-12-25

摘要:

语言竞争传播演化现象是典型的不能假设、无法进行“真实性实验”的社会科学问题,而建立在社会仿真模型基础上的计算实验是可行的方案。利用基于Agent的社会圈子网络理论并引入语言的内部词汇结构给出一种新的动态微观语言竞争社会仿真模型,其能反映语言内部结构演化涌现宏观语言态势的机制。计算实验表明:无干预调控情况下,语言共存的参数空间范围很小,很难达到共存状态,但在合适的时间窗口实施动态的调控政策可以让语言共存的参数空间显著扩大,在社会开放度高的情况下政策调控效果更好,这一发现扩展了之前人们对复杂网络语言竞争模型的认识。
 

关键词: 社会圈子, 复杂网络, 语言竞争, 计算实验

Abstract:

Language evolution is an important problem in social science field. It is a typical social science problem which cannot be applied to computation experiments before the social simulation method is introduced. We apply the social simulation method to this problem, and present a new microscopic social simulation model of language competition based on the multiagent and social circles theory. Agents of the model are characterized by vocabulary structure.
the model can show the macroscopic process of language evolution through the evolution of the vocabulary structure of speakers. We do a large number of computation experiments and the results show that the range of parameter values of language coexistence is very small and it is difficult to achieve the state of language coexistence without intervention. However, the range is significantly broadened when the intervention is undertaken within a certain time window. Furthermore, we find that the effect of intervention is better in the society with a higher openness degree. This finding extends the understanding for the language competition model of complex networks.

Key words: