摘要
当今社会技术发展日新月异,互联网对社会政治经济文化生活的影响与日俱增,也越来越得到了全社会的高度重视。十七大报告指出,“加强网络文化建设和管理,营造良好网络环境”,指明了网络文化的重要性。舆论突发事件的传播途径从传统渠道向互联网等途径转移后,出现了影响规模大、事件扩散速度快、受众范围广等新特征。而传统的人文领域研究方法只能对舆论传播的过程和个体交互的机制给出定性的描述,而无法进行定量的研究,现实中舆论突发事件的层出不穷又使得网络舆论传播机制的研究成为一个亟需解决的问题。因此,分析微观观点传播的机制,从理论上解释舆论形成的过程和传播的机制,对认识、预测和引导网络舆论有着重要的意义。
本论文从网络舆论传播的网络生长模型、网络舆论传播中的热点话题发现、舆论传播中的个体策略选择、舆论传播中的群体现象和舆论传播中的引导策略等方面研究了网络舆论的相关性质,并得到了部分结论。本论文的研究受到了教育部高等学校科技创新工程重大项目培育基金项目(707006)“网络舆情传播与预警关键技术研究”,通信与信息系统北京市重点实验室项目和北京市教育委员会共建项目的专项资助。
针对网络舆论传播的相关理论,论文的主要工作与创新点如下:
1.在传播媒介方面,针对当前舆论传播模型研究中所广泛采用的几种传播媒介及其存在的问题,通过对国内某网络社区的统计得出了网络舆论传播媒介的真实特性,提出了适合进行网络舆论传播研究的一般传播媒介模型即网络生长模型,并在此基础上对其性质进行了考察,从而给出了一个网络舆论传播媒介模型,提高了网络舆论传播模型中传播媒介的合理性和真实性。
2.在热点话题发现方面,提出了一个基于网络社区结构和用户行为模式的热点话题发现算法。该算法首先对网络社区的结构进行了研究,并对网络社区中用户的行为模式进行了统计分析,得到了网络社区中用户的活跃度、适应度等结果。通过对现有数据的处理结果,进而提出了网络社区的网络构造算法、网络社区用户适应度估计算法、网络社区用户活跃度估计算法以及网络社区热点话题检测算法。上述算法摒弃了话题跟踪与检测领域的传统方法,以用户之间的回复关系为基础,着重考察用户在网络社区中的重要性,加强了对互联网论坛中争议性、敏感性话题的发现。
3.在个体交互方面,提出和建立了以考察用户交互对舆论传播影响的舆论传播过程模型,并对其进行了实验和分析。根据实际生活中人们进行观点交互的行为,建立了具有可自行改变观点交互策略的舆论传播模型,并对参与系统演化个体的记忆进行了建模,将个体的记忆性纳入到模型考虑中。其次在该模型的基础上对不同参数下的多种情况进行了多次实验,获得了与实际舆论传播情况相符的结果,并得到了舆论传播中个体策略选择的公平性结论。
4.在交互的群体的方面,结合社会心理学领域的相关研究成果提出了一个着重考察群体规模对个体的从众性影响的舆论传播模型,该模型同时考虑了舆论传播中对立双方的群体(正方观点和反方观点)对个体观点选择的影响。对模型的研究表明该模型能很好的解释舆论传播中群体的意见如何导致观点的流行以及从众性如何导致舆论的平衡等现象。
5.在舆论引导方面,建立了舆论传播过程及其引导策略的模型,并对其进行了仿真和分析。首先根据实际生活中人们采纳观点的行为,假设个体具有从众心理,分别建立了一维和二维两种情况下的舆论传播模型,并得出了与现实社会中相吻合的同质群体聚集现象。其次在该模型的基础上对两种舆论引导方式进行了建模,并仿真和分析了上述两种模型的引导效果。仿真给出了舆论传播的趋势,对不同初始支持率的观点和不同的引导强度进行了比较。结果表明,不同的引导策略对舆论传播的最终结果有着不同的影响,适用于不同的场合。
网络舆论问题的重要性日渐凸显,其紧迫性也日益严重,该领域的研究和应用将随着社会的不断关注、学者的不断探索以及相关机构资助力度不断的加大而逐渐深入,并得到长足的发展。
Technology develops constantly in today's society.Internet affects the political, economic and cultural life increasingly which draws great attention of the whole society. Report to the Seventeenth National Congress of the Communist Party of China on Oct. 15,2007 points out this problem that "We will strengthen efforts to develop and manage Internet culture and foster a good cyber environment." The emergencies of public opinion in the Internet have the characteristics like larger scale,faster diffusion velocity and more affected people after the emergencies has transferred from traditional ways to Internet.The traditional method in communications field can just give a description of the phenomenon and quantifiable research cannot be done.The continually emergence of public opinion events urge the deeply research of network based opinion dynamics. Therefore,both the analysis of network based opinion dynamics and the theoretically explanation of formation and propagation have significant meanings.
The thesis studies the theories of network based opinion dynamics from the view of evolution process of virtual community networks,network structures and user behavior analysis based hot topic detection,personal strategy selection in opinion evolution,group size in opinion formation and the influence of intervention strategy on opinion evolution.Some schemes are provided in this thesis to resolve the issues.The research work of this thesis is supported by the Cultivation Fund of the Key Scientific and Technical Innovation Project under Grant 707006,and special foundation from Key Laboratory of Communication & Information Systems(Beijing Jiaotong University) and Beijing Municipal Commission of Education..
The main innovations of the thesis are as follows:
1.In the field of propagation media,we investigate and simulate the evolution process and topological features of the virtual community networks.We founded that the joint of nodes,joint of edges,degree distribution of networks, average degree and the correlation between the degree of nodes and its time in the network are different from the scale-free networks model.With statistics and analysis of some of the characteristics of an actual Internet forum,we propose a new network evolution algorithm,namely the virtual community networks construction algorithm.The simulation results show that the networks generated from our algorithm has the same characteristics of real virtual community networks.
2.In the field of hot topic detection,a network structures and user behavior analysis based novel method to detect the hot topics mainly focused on the Internet forum was proposed.The solution considers two important characteristics of Internet forum:the network structures and the user behavior patterns.First,we construct a network of the users' "replied to" relationships in a given Internet forum.Second,behavior patterns for all users are computed. Finally,we combine the results from first two steps to determine which topics are hot topics.Results of our empirical experiments show that our approach can identify hot topics easily and effectively.The proposed solution can enhance the controversial and sensitive topic detection.
3.In the field of individual's interaction,a model was established for opinion evolution,simulations and analysis were carried out.First,the model allowing people to change their strategies when interacting with others in opinion evolution were established based on human behavioral patterns in real life.A model of people's memory in opinion evolution was made.Second,the model with different sets of parameters was simulated for many times and the results made a good agreement with what happened in real life.Justification conclusion was achieved for personal strategy selection in opinion evolution.
4.In the field of interacting groups,a model from the social psychology points of view was proposed.The model considers both parts(positive opinions and negative opinions) of some connected people.We simulated the formation process using the proposed model,results show that the model is useful for explaining how group/herd mentality causes prevalence and how conformity lead to balance.
5.In the field of public opinion intervention strategies,models and intervention strategies were established for opinion evolution,simulations and analysis were carried out.First,one dimension and two dimension models were established based on human behavioral patterns in real life,results of these two models made a good agreement with opinion evolution in real life and aggregation phenomenon emerged in the simulations.Second,two models of intervention strategies were established based on the former opinion evolution models, simulations and analysis were done for these two models.Simulation results showed that different intervention strategies have different kinds of influence on the ultimate results of public opinion evolutions and could be used in different cases.
The research work on network based opinion dynamics will be further on with the extension of its application.
引文
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