节点文献

网络环境下信息扩散的多智能体仿真研究

Multi-agent Simulation Approach to Information Diffusion among Network

【作者】 于同洋

【导师】 肖人彬;

【作者基本信息】 华中科技大学 , 管理科学与工程, 2010, 博士

【摘要】 信息在不同的学科中具有不同的含义,本文所指的信息倾向于社会科学中对信息的理解。按照对象与层次,本文的研究范畴包括实体产品、虚拟产品、实体组织、虚拟组织四种,由此,来讨论这四方面的信息扩散问题。这四类扩散在内容上并列,在研究上关联有序。全文按照由实体到虚拟、由微观到宏观的思路来统筹全文结构。首先,针对实体产品讨论了负面口碑扩散下的新产品扩散问题,分析了新产品扩散基本特点,基于Bass经典模型,以多智能体仿真与系统动力学,基于AnyLogic建立了两种新产品扩散仿真模型,并进行相关的仿真实验及敏感性分析,为探讨新产品扩散问题提供仿真技术手段,揭示了考虑负面口碑扩散下的新产品扩散过程及特征,为企业决策提供一定的支持。另外,系统动力学的仿真结果也验证了多智能体技术的有效性和可用性,也为全文确立了以多智能体仿真为主技术上的基调。其次,针对以网游产品为代表的虚拟产品扩散进行仿真研究。以复杂网络的视角,从网络拓扑结构入手来探讨网络环境下的网游产品扩散。结合小世界网络模型建立了小世界网络环境下的网游扩散的多智能体仿真模型,进一步对虚拟产品的扩散行为特征进行分析,充实了随着时代发展的所产生的依赖于网络结构的扩散研究,揭示了信息扩散下的虚拟产品扩散规律,为辅助网游运营商决策提供了依据。再次,针对实体组织内部的隐形知识扩散,根据人际关系网络的小世界原理,提出了从网络结构入手的视角,分析了具有小世界网络效应的组织网络环境下的隐性知识扩散特点,结合认识论的保守主义、实用主义及融合主义三种倾向,提出了从个体采纳层面上考虑的三种的学习策略,利用小世界网络模型结合多智能体技术进行仿真实验,发现融合主义倾向的学习策略对组织内部的隐性知识扩散最为有利,揭示了个体层面的知识学习的基本特点,为企业的知识管理提供了一定的参考依据。最后,针对虚拟组织上的信息扩散,以社交网络这种在线虚拟社区为对象,探讨了虚拟社交网络环境下的谣言扩散问题。应用网络爬虫技术以滚雪球方式获得了真实社交网络数据,利用社会网络分析理论对该数据进行分析,揭示了这种网络的网络结构特点。以真实的网络环境为模拟环境,建立了虚拟社交网络上谣言扩散的多智能体仿真模型,分析了该类网络上的谣言扩散特征及行为,对于了解谣言扩散过程及行为提供了依据。

【Abstract】 Information has different meanings in different subject, in this paper, we consider information to be the meaning in social science. This paper research four parts concluding tangible product, virtual product, real organization and virtual organization. We research information diffusion in these four parts. This four diffusions is aligned in content and exceed each other in theory. This paper is structured as the thinking, which is form tangible to virtual, and from micro to macro.Firstly, towards tangible product, we research new product diffusion under negative word of mouth’s diffusion, analyze the characteristics of tangible product diffusion, establish two new product diffusion simulation model based on system dynamics and multi-agent simulation with classical Bass diffusion model, and then do simulation experiment and sensitivity analysis. We support a new simulation way to study new product diffusion, conclude new product diffusion characteristics and process under negative word of mouth, and also support the decision of relative enterprises. Also, The results form system dynamics verify the results form multi-agent simulation, it is the foundation of this paper to use multi-agent simulation in technical support.Secondly, towards virtual product such as net game, we simulation this virtual product’ s diffusion. From the perspective of complex network, we research net game diffusion under network’s environment with the thinking of network topology structure, establish a multi-agent simulation model of net game diffusion based on small world network theory, and we analyze the diffusion characteristics of virtual product further. This research enrich new product diffusion, conclude virtual product diffusion process and characteristics, and also support the decision of relative net game enterprises.Thirdly, towards tacit knowledge diffusion in real organization, based on human network’s small world theory and form the perspective of network topology, we analyze tacit knowledge diffusion characteristics in organization network, offer three there studying strategies on the level of individual adoption behavior, establish a multi-agent simulation model combining small world model. By simulation experiments, we conclude the confluent studying strategies is more advantaged, conclude the knowledge learning characteristics on individual adoption level, and give reference to knowledge management.Finally, towards information diffusion on virtual organization, we take online social network as research object, and research rumor diffusion between online social network. With web crawlers technology and snow ball method, We obtain real data about online social network, and we also analyze the network topology of online social network based on the above data. Based on these data, we establish rumor diffusion between online social network based on multi-agent simulation, and analyze rumor diffusion characteristics and behaviors under this network. It is provide a way to know how rumor diffuses and its diffusion process.

  • 【分类号】F224;F49
  • 【被引频次】2
  • 【下载频次】1254
节点文献中: 

本文链接的文献网络图示:

本文的引文网络