基于转发效应的自媒体网络舆情扩散
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摘要
随着无线网络技术的发展与手机网民人数的激增,以微信、微博等新媒体为平台的自媒体网络舆情逐渐取代传统媒体舆情,成为舆论场上的主导力量,并对社会的稳定产生了重要影响.基于此,首先界定自媒体网络舆情转发网络的相关概念,论述转发网络的转发效应;然后剖析自媒体网络舆情转发效应的影响因素,构建基于转发效应的自媒体网络舆情扩散模型,并在此基础上,对舆情扩散模型进行了仿真分析.通过仿真分析发现,转发网络中的超级群组是自媒体网络舆情迅速扩散的中心和节点,使得自媒体网络舆情扩散出现了明显的动态舆情级联特征,进而使其在出现、增长与稳定等阶段具有发散性特征,并以合并、超级群组和集中式拓扑结构等效应形式进行着扩散和传播.
With the development of wireless network technology and the surge of mobile internet users, the self-media internet public opinion(SMIPO) with the new media platform of WeChat, micro-blog and etc. has gradually replaced the traditional media public opinion, it has become a dominant force in the field of public opinion and has an important impact on social stability. Based on this background, this paper firstly defines the concept of SMIPO's forwarding network, discusses the forwarding effect of forwarding network, and analyzes the main impact factors of forwarding effect in SMIPO. Then this paper constructs the SMIPO diffusion model based on the forwarding effect, and simulats the public opinion diffusion model. Simulation results show that the super group, which is the central and important node of the rapid spread of SMIPO in the forwarding network, causes the obvious dynamic cascade characteristics of public opinion in the media network. In addition, the SMIPO diffusion has the divergent characteristics in the stage of appearance,amplification and stability, and diffuses and disseminates in the form of merging effects, super groups and centralized topology.
With the development of wireless network technology and the surge of mobile internet users, the self-media internet public opinion(SMIPO) with the new media platform of WeChat, micro-blog and etc. has gradually replaced the traditional media public opinion, it has become a dominant force in the field of public opinion and has an important impact on social stability. Based on this background, this paper firstly defines the concept of SMIPO's forwarding network, discusses the forwarding effect of forwarding network, and analyzes the main impact factors of forwarding effect in SMIPO. Then this paper constructs the SMIPO diffusion model based on the forwarding effect, and simulats the public opinion diffusion model. Simulation results show that the super group, which is the central and important node of the rapid spread of SMIPO in the forwarding network, causes the obvious dynamic cascade characteristics of public opinion in the media network. In addition, the SMIPO diffusion has the divergent characteristics in the stage of appearance,amplification and stability, and diffuses and disseminates in the form of merging effects, super groups and centralized topology.
引文
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[23] Kwak H, Lee C, Park H, et al. What is twitter, a social network or a news media?[C]:Proc of the 19th Int Conf on World Wide Web. New York, 2010:591-600.
[24]裘江南,刘丽丽,董磊磊.基于贝叶斯网络的突发事件链建模方法与应用[J].系统工程学报, 2012, 27(12):739-750.(Qiu J N, Liu L L, Dong L L. Modeling method and application of emergent event chain based on bayesian network[J]. J of Systems Engineering, 2012, 27(12):739-750.)
[25]周涛,汪秉宏,韩筱璞,等.社会网络分析及其在舆情和疫情防控中的应用[J].系统工程学报, 2010, 25(6):742-754.(Zhou T, Wang B H, Han Y P, et al. Social network analysis and its application in the prevention and control of propagation for public opinion and the epidemic[J]. J of Systems Engineering, 2010, 25(6):742-754.)
[26]程威,钟华,孙娇华.网络论坛中发帖行为复杂性研究[J].系统工程学报, 2009, 24(4):385-391.(Cheng W, Zhong H, Sun J H. Research on complexity of posts in network forums[J]. J of Systems Engineering,2009, 24(4):385-391.)
[27] Zhou Ya-dong, Zhang Bei-bei, Li Jing-yu, et al.Analyzing and modeling dynamics of information diffusion in microblogging social network[J]. J of Network and Computer Applications, 2016, 31(9):1-11.
[28] Han W, Zhu X, Zhu Z, et al. A comparative analysis on weibo and twitter[R]. Beijing:Tsinghua University Science and Technology Laboratory(STL), 2016.
[29]柳赛男,陈明亮.基于文化算法的多agent联盟在网络舆情监测中的应用[J].控制与决策, 2014, 29(9):1724-1728.(Liu S N, Chen M L. Application of multi-agent coalition in network public opinion monitoring based on cultural algorithm[J]. Control and Decision, 2014, 29(9):1724-1728.)
[2] Andrea E. Automatic generation of lexical resources for opinion mining:Models, algorithms and applications[D].Pisa:University of Dipisa College of Computer Science and Technology, 2008.
[3] Garcia R, Porrata A. Dynamic hierarchical algorithms for document clustering[J]. Pattern Recognition Letters,2010, 31(12):169-177.
[4] Gurcun A C. Using microglogs for cowdsourcing and public opinion-mining[D]. Buffalo:State University of New York School of Information Engineering, 2010.
[5] Mulde K. The dynamics of public opinion on nuclear power:Interpreting an experiment in the Netherlands[J].Technological Fore-casting&Social Change, 2012,179(8):1513-1524.
[6] Deanne K, Katharine H, Honert R, et al. Nuclear power in Australia:A comparative analysis of public opinion regarding climate change and the Fukushima disaster[J].Energy Policy, 2014, 65(2):644-653.
[7] Drezewski R, Sepielak J, Filipkowski W. The application of social network analysis algorithms in a system supporting money laundering detection[J]. Information Sciences, 2015, 295(12):18-32.
[8]刘志明,刘鲁.微博网络舆情中的意见领袖识别及分析[J].系统工程, 2011, 29(6):8-16.(Liu Z M, Liu L. Recognition and analysis of opinion leaders in microblog public opinions[J]. Systems Engineering, 2011, 29(6):8-16.)
[9]宋彪,朱建明,黄启发.基于群集动力学和演化博弈论的网络舆情疏导模型[J].系统工程理论与实践, 2014,34(11):2984-2994.(Song B, Zhu J M, H Q F. The internet public opinion grooming model based on cluster dynamics and evolutionary game theory[J]. Systems Engineering—Theory&Practice, 2014, 34(11):2984-2994.)
[10]曹学艳,张仙,刘樑,等.基于应对等级的突发事件网络舆情热度分析[J].中国管理科学, 2014, 22(3):82-89.(Cao X F, Zhang X, Liu L, et al. Research on internet public opinion heat based on the response level of emergencies[J]. Chinese J of Management Science, 2014,22(3):82-89.)
[11]林晓静,庄亚明,孙莉玲.具有饱和接触率的SEIR网络舆情传播模型研究[J].情报杂志, 2015, 34(3):150-154.(Lin X J, Zhang Y M, Sun L L. Research on network public opinions based on SEIR model with saturating incidence rate[J]. J of Intelligence, 2015, 34(3):150-154.)
[12]兰月新,董希琳,曾润喜,等.信息异化视角下网络舆情衍生效应模型研究[J].情报杂志, 2015, 34(1):139-149.(Lan Y X, Dong X L, Zeng Y X, et al. Research on effects model of derivative of network public opinion from the perspective of information alienation[J]. J of Intelligence,2015, 34(1):139-149.)
[13]王晰巍,邢云菲,赵丹,等.基于社会网络分析的移动环境下网络舆情信息传播研究[J].图书情报工作,2015, 57(4):14-22.(Wang X W, Xing Y F, Zhao D, et al. The of network public opinion dissemination with social network analysis[J]. Library and Information Service, 2015, 57(4):14-22.)
[14]林芹,郭东强.基于传播主体特性企业网络舆情传播的系统动力学仿真研究[J].情报科学, 2017, 35(4):54-67.(Lin Q, Guo Q D. System dynamics simulation research of enterprise network public opinion dissemination[J].Intelligence Science, 2017, 35(4):54-67.)
[15] Zhang Zi-ke, Liu Chuang, Zhan Xiu-xiu, et al. Dynamics of information diffusion and its applications on complex networks[J]. Physics Reports, 2016, 19(7):1-34.
[16]王金龙,刘方爱,朱振方.一种基于用户相对权重的在线社交网络信息传播模型[J].物理学报, 2015, 64(5):050501-01-11.(Wang J L, Liu F A, Zhu Z F. An information spreading model based on relative weight in social network[J]. Acta Physica Sinica, 2015, 64(5):050501-01-11.)
[17]周东浩,韩文报. DiffRank:一种新型社会网络信息传播检测算法[J].计算机学报, 2014, 37(4):884-893.(Zhou D H, Han W B. DiffRank:A novel algorithm for information diffusion detection in social networks[J].Chinese J of Computers, 2014, 37(4):884-893.)
[18] Liu Chuang, Zhang Zi-ke. Information spreading on dynamic social networks[J]. Commun Nonlinear Sci Numer Simulat, 2014, 19(9):896-904.
[19]李林,孙军华.基于社会网络冲突信息传播的群体特征[J].系统工程理论与实践, 2014, 34(1):207-214.(Li L, Sun J H. Population characteristics based on conflict information spreading on social network[J]. Systems Engineering—Theory&Practice, 2014, 34(1):207-214.)
[20] Liu Chuang, Zhan Xiu-xiu, Jia Fa, et al. How events determine spreading patterns:Information transmission via internal and external in uences on social networks[J].New J of Physics, 2015, 17(11):1-10.
[21]韩佳,肖如良,胡耀,等.在线社交网络中信息传播模式的特征分析[J].计算机应用, 2013, 33(1):105-107.(Han J, Xiao Y L, Hu Y, et al. Characteristic analysis of information propagation pattern in online social network[J]. J of Computer Applications, 2013, 33(1):105-107.)
[22]包卫军,徐成贤.基于SV-Copula模型的相关性分析[J].统计研究, 2008, 25(10):100-104.(Bao W J, Xu C X. Analysis of correlation based on the SV-copula model[J]. Statistical Research, 2008, 25(10):100-104.)
[23] Kwak H, Lee C, Park H, et al. What is twitter, a social network or a news media?[C]:Proc of the 19th Int Conf on World Wide Web. New York, 2010:591-600.
[24]裘江南,刘丽丽,董磊磊.基于贝叶斯网络的突发事件链建模方法与应用[J].系统工程学报, 2012, 27(12):739-750.(Qiu J N, Liu L L, Dong L L. Modeling method and application of emergent event chain based on bayesian network[J]. J of Systems Engineering, 2012, 27(12):739-750.)
[25]周涛,汪秉宏,韩筱璞,等.社会网络分析及其在舆情和疫情防控中的应用[J].系统工程学报, 2010, 25(6):742-754.(Zhou T, Wang B H, Han Y P, et al. Social network analysis and its application in the prevention and control of propagation for public opinion and the epidemic[J]. J of Systems Engineering, 2010, 25(6):742-754.)
[26]程威,钟华,孙娇华.网络论坛中发帖行为复杂性研究[J].系统工程学报, 2009, 24(4):385-391.(Cheng W, Zhong H, Sun J H. Research on complexity of posts in network forums[J]. J of Systems Engineering,2009, 24(4):385-391.)
[27] Zhou Ya-dong, Zhang Bei-bei, Li Jing-yu, et al.Analyzing and modeling dynamics of information diffusion in microblogging social network[J]. J of Network and Computer Applications, 2016, 31(9):1-11.
[28] Han W, Zhu X, Zhu Z, et al. A comparative analysis on weibo and twitter[R]. Beijing:Tsinghua University Science and Technology Laboratory(STL), 2016.
[29]柳赛男,陈明亮.基于文化算法的多agent联盟在网络舆情监测中的应用[J].控制与决策, 2014, 29(9):1724-1728.(Liu S N, Chen M L. Application of multi-agent coalition in network public opinion monitoring based on cultural algorithm[J]. Control and Decision, 2014, 29(9):1724-1728.)