Study on the Network of Information Dissemination between Network Media——A Case Study of Food Safety Micro-blog Public Opinion

Abstract

Abstract:

Information on the platform of microblog disseminates primarily through social ties. Based on the relations among micro-blog media, such as forwarding, information dissemination network forms, whose structure determines the effectiveness of information dissemination. Using social network analysis, the paper explores the structure of whole network and sub-network and the factors that influence media's location and the capability of disseminating information. The study indicates that (1)the network of information dissemination between network media is sparse and scale-free. The stability of the network is affected by a small number of media, such as paper media microblog, TV media microblog; (2)the phenomenon of subgroup is exhibited in the network, and distribution of media within the subgroup is regional; (3) media's capability of disseminating information is closely related to its professionalism, authority and participation.

Key words: information dissemination, media micro-blog, social network analysis, micro-blog public opinion

Hong Xiaojuan, Jiang Nan, Hong Wei, Huang Weidong. Study on the Network of Information Dissemination between Network Media——A Case Study of Food Safety Micro-blog Public Opinion[J]. , 2016, 28(8): 115-124.

References

[1] 姜景,李丁,刘怡君.基于微博舆论生态的突发事件管理策略研究[J].管理评论,2015,27(4):48-56
[2] Yang J.,Counts S.Predicting the Speed,Scale,and Range of Information Diffusion in Twitter[J].ICWSM,2010,10:355-358
[3] 陈昌凤.媒体微博:公共事件中的舆论引导者[J].新闻与写作,2013,(11):83-85
[4] 刘文,李强.食品安全网络舆情监测与干预研究初探[J].中国科技论坛,2012,(7):44-49
[5] Mehrabian A.,Pourmiri A.Randomized Rumor Spreading in Poorly Connected Small-World Networks[J].Random Structures&Algorithms,2016,49(1):185-208
[6] Giakkoupis G.,Sauerwald T.,Stauffer A.Randomized Rumor Spreading in Dynamic Graphs[M].Automata,Languages,and Programming.Springer Berlin Heidelberg,2014
[7] Han S.,Zhuang F.,He Q.,et al.Energy Model for Rumor Propagation on Social Networks[J].Physica A:Statistical Mechanics and Its Applications,2014,394:99-109
[8] Zhang N.,Huang H.,Su B.,et al.Dynamic 8-State ICSAR Rumor Propagation Model Considering Official Rumor Refutation[J].Physica A:Statistical Mechanics and its Applications,2014,415:333-346
[9] Zhang N.,Huang H.,Su B.,et al.Information Dissemination Analysis of Different Media towards the Application for Disaster Pre-warning[J].PLOS ONE,2014,9(5):e98649
[10] Crokidakis N.Effects of Mass Media on Opinion Spreading in the Sznajd Sociaophysics Model[J].Physica A:Statistical Mechanics and Its Application,2012,391(4):1729-1734
[11] 喻国明.中国媒体官方微博运营现状的定量分析[J].新闻与写作,2013,(1):84-87
[12] 涂光晋,陈敏.媒体微博的内容特色与生产机制研究——以三家报纸的官方微博为例[J].现代传播:中国传媒大学学报,2013,(3):35-40
[13] 李玲.微博时代传统媒体的挑战、机遇与对策[J].理论探索,2011,(3):91-93
[14] Zhao L.,Wang Q.,Cheng J,et al.The Impact of Authorities' Media and Rumor Dissemination on the Evolution of Emergency[J].Physica A:Statistical Mechanics and its Applications,2012,391(15):3978-3987
[15] 朱恒民,刘凯,卢子芳.媒体作用下互联网舆情话题传播模型研究[J].现代图书情报技术,2013,29(3):45-50
[16] 陈福集,叶萌.系统动力学视角下政府回应网络舆情的能力提升研究[J].情报杂志,2013,32(11):121-127
[17] 刘军.社会网络分析导论[M].北京:社会科学文献出版社,2004
[18] 张利华,闫明.基于SNA的中国管理科学科研合作网络分析——以《管理评论》(2004-2008)为样本[J].管理评论,2010,22(4):39-46
[19] 杨辉,尚智丛.微博科学传播机制的社会网络分析——以转基因食品议题为例[J].科学学研究,2015,33(3):337-346
[20] 谭跃进,吴俊,邓宏钟.复杂网络中节点重要度评估的节点收敛方法[J].系统工程理论与实践,2006,26(11):79-83
[21] 康伟.突发事件舆情传播的社会网络结构测度与分析——基于"11·16校车事故"[J].中国软科学,2012,(7):169-178
[22] 康伟,陈茜,陈波.基于SNA的政府与非政府组织在公共危机应对中的合作网络研究——以"4·20"雅安地震为例[J].中国软科学,2014,(5):141-150
[23] 赵金楼,成俊会.基于SNA的突发事件微博舆情传播网络结构分析——以"4·20四川雅安地震"为例[J].管理评论,2015,27(1):148-157
[24] Albert R.,Jeong H.,Barabasi A.L.Diameter of the World-Wide Web[J].Nature,1999,401(6):130-131
[25] Newman M.E.J.Scientific Collaboration Networks.Ⅱ.Shortest Paths,Weighted Networks,and Centrality[J].Physical Review E,2001,64(1):016132
[26] 焦璨,张楠楠,张敏强,等.基于社会网络分析的心理学科研人员合作网络研究[J].吉林大学社会科学学报,2014,54(4):163-170
[27] 洪巍,吴林海.中国食品安全网络舆情事件特征分析与启示——基于2009-2011年的统计数据[J].食品科技,2013,38(8):328-332