几类网络舆情研判模型及应对策略研究

发布时间：2018-01-22 09:53

  本文关键词： 大数据 网络舆情 研判模型 应对策略　出处：《东南大学》2016年博士论文　论文类型：学位论文

【摘要】：随着各种智能移动终端设备的普及以及各种即时通讯软件和平台的发展,我国互联网进入Web2.0时代。互联网改变了传统的舆情表现方式,把网络舆情推到了反映民众情绪和行为倾向的前台。网络平台以开放的空间形态,成为个体和社会组织参政议政、表达态度、发表言论的公共平台,成为快速传递信息和传达民意的通道,成为各种社会思潮交锋、各种利益诉求集散和多种意识形态较量的阵地,网络舆情研判和应对成为当今网络社会一项新的重要任务。当前网络舆情研究,面临的主要问题是信息冗余和信息传播方式革命性变化所带来的夹杂大量噪音的海量数据的处理,导致了基于传统的数据挖掘技术无法适应新的要求,而且缺乏对不同网络舆情的细分,缺乏针对不同特质的网络舆情建立不同的分析模型进行分析,目前市场上的网络舆情分析软件以同一模型笼统应对不同特征的网络舆情,存在较大局限性。本文以大数据环境为背景,在对国内外相关研究现状进行归纳分析的基础上,主要针对网络谣言、高校学生网络舆情和突发公共卫生事件等三类典型的网络舆情,采用定性分析和定量分析相结合的方法,围绕网络舆情的传播机制、预警决策机制和演化机理开展一系列的研究。在基于模型分析的基础上,提出针对不同类型网络舆情的管理和应对策略。首先,基于传染病动力学理论,文中构建了具有饱和接触率的网络谣言传播研判模型和非线性接触率网络谣言传播研判模型,利用动力系统平衡点理论与稳定性理论,对网络谣言进行了定量分析。研究结果表明,在网络谣言传播中存在一个阈值R0,当R01时,系统将存在内部非零平衡点,即如任由谣言发展,会在系统中大面积爆发开来;当网民群体人数服从Logistic曲线时,新增加的网民不会对网络谣言的传播造成影响;由于阈值对心理作用系数的变化非常敏感,因此采取措施增大心理作用系数可以高效管理网络谣言的扩散;披露不实信息以及不实信息传播者,其管理效率要远高于正向宣传。其次,针对突发公共卫生事件网络舆情传播的特点,引入Deffault模型,建立了有向加权动态网络结构模型,利用Matlab工具对所建立的网络舆情观点演化模型进行仿真分析,验证了所建立的模型的有效性和合理性,还研究了影响网络舆情观点演化传播的主要因素。结果表明,有向加权动态BBV网络是无标度网络,符合在线社会网络结构的特性。模型分析还发现,政府的态度r、媒体的关注程度λ等都能对网络舆情产生显著影响。因此,政府及主要公众媒体利用自身权威性及时披露信息,加强疏导,可以有效消除社会恐慌,稳定社会局面。接着,针对高校学生网络舆情预警级别的评判,构建了基于直觉模糊推理和层次分析法的网络舆情定性和定量评判模型。关于运用直觉模糊推理判断网络舆情预警等级,将话题重要性、公众反应和公众与话题联系作为直觉模糊推理的参与因素,用直觉模糊综合评判法计算每个因素的隶属度,将最贴近的直觉模糊集作为网络舆情预警等级,运用直觉模糊集理论构建了网络舆情预警级别判定模型。对于运用层次分析法判定网络舆情预警等级,利用层次分析法将目标分解为多指标层次,引入专家打分法确定各级指标权重,构造了反映高校网络舆情传播深度和广度的定性与定量相结合的指标体系,在对各级指标具体权重值进行一致性检验后,根据所构建的模型计算网络舆情研判的指标值S,根据S值所对应的阈值区间,确定应启动的预警级别,进而通过分析其变化的基本特征,掌握其发展态势,揭示出问题的本质所在,预测出舆情的进一步走向,可以帮助决策者做出正确决策,对舆论进行引导和控制。实证研究表明,以网络数据的收集整理和专家决策人员的理性判断为切入点,通过定量和定性相结合,可以及时准确地判断舆情级别,为及早启动预警流程和进行引导干预,有效控制舆情发展态势提供支持。本文最后还进行了案例分析。选取天津滨海新区爆炸事件、湖南大学研究生违规转学事件作为典型案例,以本文中的理论研究为基础,研究了网络谣言的传播机制、网络舆情的预警机制和网络舆情意见的演化过程,分别采集谣言和公共卫生影响的关键词,对事件进行描述,将特征数据代入模型进行求解,并对结果进行分析。研究结果表明,不同类型的网络事件具有较为明显的内在规律和特点,本文所建立网络舆情研判模型是有效的。
[Abstract]:With a variety of intelligent mobile terminal equipment and a variety of popular instant messaging software platform and the development of China's Internet into the Web2.0 era. The Internet has changed the traditional public opinion expression, network public opinion to reflect public sentiment and behavior tendency of the front desk. The network platform to open space, become the individual and social organization participation besides, the expression of attitude, the public platform of speech, become the rapid transmission of information and communication channels of public opinion, as against a variety of social thought, various interests distribution and various ideological battle positions, network public opinion judged and respond to today's social network become a new important task. The current network public opinion research, is the main problem facing with a lot of noise processing of massive data of information redundancy and information dissemination way brings revolutionary change, based on the traditional lead The data mining technology can not adapt to the new requirements, and the lack of network public opinion segmentation, lack of public opinion against the network of different characteristics of different models of analysis, the current network of public opinion on the market analysis of network public opinion in the same general software model with different characteristics, there is a big limitation. Based on the background of large data environment, the foundation of analysis on the related research at home and abroad, mainly for Internet rumors, the college students network public opinion and public health emergencies and other three kinds of typical network public opinion, using the method of qualitative analysis and quantitative analysis, on the transmission mechanism of network public opinion, to carry out a series of studies on the early warning decision the mechanism and evolution mechanism. Based on the model analysis, proposed management and coping strategies of different types of network public opinion. Firstly, based on the Epidemic dynamics theory, this paper constructs a network spread rumors saturated contact rate evaluation model and nonlinear contact rate of network rumor judged by dynamic system model, equilibrium theory and stability theory, the network rumors are quantitatively analyzed. The results show that there is a threshold of R0 in the network spread rumors, when R01 when the system will exist within the nonzero equilibrium points, such as let the rumor in the system development, will the outbreak of a large area of it; when users group number obeys the Logistic curve, the impact of the increase in the spread of new users will not be on the network rumors; because the threshold is very sensitive to changes on the psychological factor, so take measures to increase the psychological effect of diffusion coefficient can be the efficient management of network rumor; the disclosure of false information and false information spread, the management efficiency is much higher than that of the positive publicity. Secondly, according to the The characteristics of public health emergency network public opinion dissemination, the introduction of the Deffault model, based on weighted dynamic network structure model, on the view of network public opinion evolution model is analyzed and simulated by using Matlab tools, the results prove that the model is effective and reasonable, also studied the main factors affecting the evolution of the network public opinion dissemination view. The results show that the directed weighted dynamic BBV network is a scale-free network, with the characteristics of online social network structure model. The analysis found that the attitude of the government of R, the media attention degree lambda can have a significant impact on the Internet public opinion. Therefore, the government and public media using its own authority timely disclosure of information and strengthen counseling, can effectively eliminate social panic, stable social situation. Then, according to the university student network public opinion warning level evaluation, construct intuitionistic fuzzy reasoning based on The network public opinion qualitative and quantitative evaluation model analysis method and hierarchy. On the application of intuitionistic fuzzy reasoning to judge the warning level of the network of public opinion, the topic significance, the reaction of the public and public topics and links as intuitionistic fuzzy reasoning participation factor, membership in intuitionistic fuzzy comprehensive evaluation method to calculate each factor, will be the most close to the intuitionistic fuzzy sets as the warning level of network public opinion, fuzzy set theory to construct the warning level network public opinion judgment model for use of intuition. Determined by using AHP and warning level network public opinion, using AHP method to decompose the goal for the multi index level, introducing expert scoring method to determine the weights at all levels, construct the index system to reflect the qualitative and quantitative analysis of university network public opinion dissemination the depth and breadth of the combination, in the specific weight of all index value of the consistency test, according to the construction of Calculation model of network public opinion judged the index value of S, according to the S value corresponding to the threshold interval should be determined to start early warning level, and then through the analysis of the basic characteristics of the changes in the grasp of its development trend, reveal the essence of the problems and predict further towards the public opinion, can help decision-makers to make correct decisions on public opinion to guide and control. The empirical study shows that in a rational judgment of network data collection and expert decision makers as the starting point, through a combination of quantitative and qualitative, can timely and accurately determine the level of public opinion, to start early warning process and guide intervention, effective control of support the development trend of public opinion. In the end of case analysis. Taking Tianjin Binhai New Area bombing, graduate students of Hunan University as a typical case of illegal transfer events, based on theoretical research in this paper is based on The network rumor spreading mechanism, the evolution process of the early warning mechanism of network public opinion and network public opinion, keyword rumors and public health impact were collected. The description of the event, will feature data into the model, and the results were analyzed. The results show that different types of network events have the intrinsic rules and characteristics obviously, this network of public opinion judged model is effective.

【学位授予单位】：东南大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：D669;C912.63
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本文编号：1454352