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官方信息在现实生活和虚拟网络中的扩散对谣言传播具有双重影响。本文建立多层网络传播模型研究跨境电商新政策错误解读这一谣言传播问题,模型上层为虚拟网络传播层(虚拟层),下层为现实社会传播层(现实层),个体根据各自社交网络和行为习惯接收官方信息来控制多层网络谣言传播。文章根据平均场方法分析该模型的演化过程和传播阈值,采用无标度网络进行仿真验证了理论分析传播动力学行为的正确性,结果表明,官方信息对虚拟层和社会层谣言的控制都具有积极作用,官方信息的掌握程度对社会谣言传播有显著性影响,且当官方信息的网络传播达到一定规模时,能够有效约束现实社会个体行为,进而达到虚拟层和现实层对谣言控制的同向促进作用。  相似文献   

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新冠肺炎疫情的爆发伴随着大量的谣言在社交媒体平台传播,对网络秩序和社会稳定产生了不良影响.已有的疫情相关社交媒体谣言传播量化分析研究仅对谣言内容等单一传播要素展开分析,而忽略了构成信息传播的其他基础要素,包括传播者、受众以及传播效果等.同时,这些研究的谣言数据与真实的社交媒体谣言数据也存在分布偏差和信息缺失.因此,基于新浪微博平台对新冠疫情相关社交媒体谣言的传播展开更加全面的量化分析.具体而言,首先对谣言传播内容进行分析,包括其主题分析、涉及地区分析、事件倾向性分析以及情感分析;进一步对谣言参与用户进行分析,将参与用户分为3类:造谣者、传谣者和辟谣者,并分别对其基础属性、关注主题、个体情绪以及自网络属性进行探究;最后对谣言引发舆情进行分析,探究其情感的整体分布、与主题、关键词和地区的关系、以及情感的演变规律.该研究首次从信息传播的各个基础要素层面对疫情相关的社交媒体谣言传播展开量化分析,不仅对新冠肺炎疫情相关谣言传播有了更全面深刻的认识,同时对突发公共事件的谣言研究和谣言治理也具有十分重要的价值.  相似文献   

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现有的谣言传播模型无法描述不同节点对谣言传播概率的影响,从而造成了谣言传播模型无法真实地描述现实社交网络中的谣言传播,进而影响了对网络中谣言传播的控制。针对这一问题,在SIR传播模型的基础上考虑了谣言在不同节点之间的传播概率,并且分析了不同节点对传播概率的影响情况,从而建立了社交网络中考虑网络节点自身影响的谣言传播模型。最后,通过将改进的谣言传播模型与常用的SIR模型进行对比,实验结果显示,提出的改进模型可以较快地控制网络中谣言的传播。  相似文献   

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谣言传播中个体模型的研究,主要从个体的主体思维过程出发,采用BDI模型进行建模研究,谣言传播网络中的个体角色完全对等。但是在实际的谣言传播网络中,由于政府部门等公共个体的行为对普通个体的行为具有很大的影响,所以谣言传播中个体的角色并不完全对等。在公共权威(Public Authority,PA)对个体影响的基础上,把公共权威引入BDI,提出基于公共权威的PA-BDI模型,进行不对等谣言传播网络中个体模型的研究。  相似文献   

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随着信息传播方式的改变,通过信息推荐平台的谣言信息传播成为了谣言传播的重要方式,构建推荐模式下的谣言传播模型对网络谣言的治理具有积极作用。考虑到推荐机制对用户的分割效应,在谣言传播过程中根据人物相似性将网络用户划分在不同的传播域,定义了传播域中用户与信息的交互方式,提出了一种基于谣言信息热度和平台用户密度的谣言传播模型,并对影响谣言信息传播的因素进行了仿真分析。通过仿真发现:在推荐机制下,人们对信息的接受率主要是受信息本身影响;在推荐平台上,增大谣言信息传播阈值有利于阻止谣言的传播;谣言的接受率越大,对辟谣信息的加入时间要求越高。  相似文献   

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社交网络中谣言的肆意传播给网络安全以及社会稳定带来了全新的挑战,如何科学地认识和掌握谣言传播、扩散的内在规律,并对谣言进行有效地控制具有非常重要的学术意义和社会意义。文章首先在充分分析目前谣言传播模型的基础上,引入谣言正向感染及负向感染两个感染状态,提出更适用于描述谣言传播的SPNR模型;其次,基于SPNR模型,设计谣言传播SPNR算法,实现谣言传播演化过程的仿真;另外,利用数值仿真的方法,分析了模型主要参数对谣言传播关键指标的影响效果,为制定有效的谣言控制策略提供了可靠的依据;最后,从定性和定量两个角度验证了SPNR模型基本假设的准确性,同时通过将SPNR模型模拟效果与新浪微博实证结果进行对比试验的方式,验证了SPNR谣言传播模型的适用性。  相似文献   

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网络谣言污染网络环境,扰乱社会秩序,影响社会稳定,损害国家形象。如何加大对其监管和打击力度,有效防范和控制网络谣言的制造和传播是一个重大课题。文章分析了当前我国网络谣言传播的机理,并基于这些机理,提出了相应的治理对策。  相似文献   

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为深入了解谣言传播规律,提出一种适用于突发事件人群聚集场所的谣言传播模型。针对突发事件聚集个体的不同动机,将聚集人群划分为6种不同状态,并以个体的信任度、谣言接受度和社会恶劣认知度体现个体的特征,同时分析闹事者占比、普通市民个体特征、事件处置方式等因素对谣言传播过程产生的影响。实验结果表明,该模型的个体社会认知度和事件处置方式会影响谣言传播速度,而初始传播者的占比和聚集人群的社会关系对谣言传播影响较小。  相似文献   

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为解决现有谣言检测模型对时间信息利用不充分的问题,同时验证利用谣言传播的社区结构特征可以提高谣言检测模型的性能,提出一种融合动态传播和社区结构的社交媒体谣言检测模型Dy_PCRD(rumor detection model based on dynamic propagation and community structure),一方面使用图卷积网络提取谣言传播的结构特征,另一方面先根据谣言内容和传播结构划分话题社区,再使用一种新型的注意力计算方法提取谣言的社区结构特征,将二者分别输入时间注意力单元对其动态变化规律进行建模,最后基于所获得的嵌入表示对谣言进行分类。三个公开数据集上的实验结果表明,在相同条件下,相较于基线模型,其准确率及其他各评价指标均有所提升,验证了社区结构特征、动态性特征以及相关注意力计算方法对提升谣言检测模型性能的有效性。  相似文献   

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During terror attacks, information with unknown credibility might circulate and people use rumors to compensate for information gaps. On 06.12.2014, three teenagers were kidnapped from a bus station in the West Bank and found dead after several days. A gag order was issued, causing interest in alternative sources of information. This study investigated how information spread through WhatsApp during the search operation using a participatory research approach. 13 rumors circulating on WhatsApp were collected, nine of which were verified, and found to be true. A web-based survey revealed that 61.1% of 419 respondents received information regarding the kidnapping through WhatsApp; 38.9% through Facebook. Sources of two rumors and participation of emergency authorities in rumor dissemination were identified. Some rumors originated from the family and community of the abductees, while other WhatsApp messages included information and names of two abductees, which were not public at the time. When emergency authorities share unconfirmed information, it is perceived as more credible than information spread by citizens. During the operation, official representatives did not correct or refute any rumors. Locating the source of a rumor is challenging and thus it is important to actively investigate rumors in real-time in order to locate the source.  相似文献   

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文章通过对多媒体和书籍媒介的分析比较,归纳出现代书籍的新特点并有针对性地提出新的设计思路、方法以及技术手段,为书籍设计实践提供理论依据。多媒体时代语境下的书籍设计需要借鉴与改变。取长补短才能得到更好的发展,呈现出时代的面貌。  相似文献   

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根据突发事件应急处理系统的现状及特点,并充分考虑到未来的发展趋势,提出了基于3G网络的应急处理系统的实现方案及现场实施方案。  相似文献   

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Web-based communication via social networking sites has become an integral method of communication, raising the question of whether the well-established Attachment Theory remains applicable to modern relationships. This communication shift is also likely to affect the information dissemination dynamic; i.e., how internal attachment working models relate to virtual modes of communication. Three studies (354 participants in total, median age 27) examined the applicability of Attachment Theory to web-based social network communications. Using self- report measures (Study 1) and an experimental simulation (Study 2), the results indicate that attachment security level predicts an individual’s number of social ties and willingness to initiate web-based relationships. Secure individuals emerged as best situated to become social hubs. Study 3 reveals that a decrease in avoidance scores predicts an increased willingness to deliver information to others. Anxious participants exhibited less willingness to deliver highly threatening information but more willingness to deliver neutral information to others.These findings support the applicability of attachment internal working models to predicting web-based social network communication, and suggest that Attachment Theory can be a predictor of the dynamics of web-based dissemination of information.  相似文献   

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朱冠桦  蒋国平  夏玲玲 《计算机科学》2016,43(2):135-139, 143
社交网络中谣言的爆炸性传播现象已引起了研究人员的关注,其传播机制及相应模型的研究对于控制网络谣言的传播至关重要。 受社会网络中的从众现象的启发,在传统SIR谣言传播模型的基础上,考虑到社交网络中的谣言具有全局信息特征,其从众效应具有个体差异性,以及社交网络的规模和拓扑特性(均质和异质网络)对谣言传播的影响,首先建立了两个适用于均质网络和异质网络的改进的SIR谣言传播模型动力学方程组;然后利用蒙特卡罗方法对谣言传播演化过程进行了仿真,结果表明,相对于传统模型,基于这两个方程组的模型能有效体现社交网络中的从众现象对于谣言传播的增幅作用。此外,改进的模型揭示并体现了实际社交网络中谣言传播在从众现象的影响下的规律:蛊惑性较强的谣言传播率提升空间有限,增幅效应较小;蛊惑性较弱的谣言提升空间大,转发的人越多,从众效应的增幅越大,传播的速度越快,爆发到顶峰的时间越短;社交网络规模的增大可以显著削弱从众现象对谣言的增幅作用。  相似文献   

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Social media has become mainstream in recent years, and its adoption has skyrocketed. Following this trend among the general public, scholars are also increasingly adopting these tools for their professional work. The current study seeks to learn if, why and how scholars are using social media for communication and information dissemination, as well as validate and update the results of previous scholarship in this area. The study is based on the content analysis of 51 semi-structured interviews of scholars in the Information Science and Technology field. Unlike previous studies, the current work aims not only to highlight the specific social media tools used, but also discover factors that influence intention and use of social media by scholars. To achieve this, the paper uses the Unified Theory of Acceptance and Use of Technology (UTAUT), a widely adopted technology acceptance theory. This paper contributes new knowledge to methodological discussions as it is the first known study to employ UTAUT to interpret scholarly use of social media. It also offers recommendations about how UTAUT can be expanded to better fit examinations of social media use within scholarly practices.  相似文献   

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随着社交网络平台的发展,社交网络已经成为人们获取信息的重要来源.然而社交网络的便利性也导致了虚假谣言的快速传播.与纯文本的谣言相比,带有多媒体信息的网络谣言更容易误导用户以及被传播,因此对多模态的网络谣言检测在现实生活中有着重要意义.研究者们已提出若干多模态的网络谣言检测方法,但这些方法都没有充分挖掘出视觉特征和融合文...  相似文献   

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ABSTRACT

Social media have great power to spread information, and this is particularly noticeable when an emergency occurs. The extraction of accurate information from social media can offer an important resource for emergency management, both in terms of decision-making and increasing situational awareness. This paper describes a conceptual framework for the development of applications to treat messages from social media. It is designed to select, classify and prioritise, using parameters, messages containing information that is relevant to the emergency context. It allows a team to act on this information and to generate rescue actions that contribute to the emergency solution. It has a collaborative bias, providing perceptual, coordination and communication mechanisms. We also present an instantiation and the simulation of its use in the treatment of tweets (Twitter messages) about two emergencies: an earthquake in Mexico City (19/09/2017) and a California fire (December, 2017). The volume of messages is enormous, but most of them do not present significant value to the emergency response. We categorised those that contained relevant information. With only 2% of the tweets, it was possible to identify and prioritise messages with potential to aid in response and rescue operations.  相似文献   

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