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New Technology of Library and Information Service  2015, Vol. 31 Issue (5): 24-33    DOI: 10.11925/infotech.1003-3513.2015.05.04
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Research on Micro-blog Public Opinion Information Interaction Model Under the Background of Big Data
Lan Yuexin, Dong Xilin, Su Guoqiang, Qu Zhikai
Keb Laboratory of Firefighting and Rescue Technology of MPS, The Chinese People's Armed Police Forces Academy, Langfang 065000, China
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[Objective] By building a mathematical model, this paper studies the information interaction between micro-blog and other network media under the background of big data. [Methods] Analyze the information interactive features of micro-blog public opinion, define the information interaction coefficient, and establish the differential equation model of micro-blog information interaction. [Results] Using Matlab numerical simulation and six cases of network public opinion to analyze the feature of the model and validate the model, it is concluded that to build information interaction mechanism is the key for the government to response network public opinion under the background of big data. [Limitations] The research only builds the regular model of micro-blog information interaction, not considering the situation when the negative public opinions like Internet rumors spreads rapidly and widely. [Conclusions] The results can help the government take measures when facing complex micro-blog public opinion, and also provide some references for the further research on information interaction problem of public opinion.

Key wordsBig date      Micro-blog public opinion      Information interaction      Mathematical model     
Received: 17 November 2014      Published: 11 June 2015
:  TP391  

Cite this article:

Lan Yuexin, Dong Xilin, Su Guoqiang, Qu Zhikai. Research on Micro-blog Public Opinion Information Interaction Model Under the Background of Big Data. New Technology of Library and Information Service, 2015, 31(5): 24-33.

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[1] 中国互联网络信息中心. 第34次中国互联网络发展状况统计报告[R/OL]. [2014-07-26]. hlwfzyj / hlwxzbg / hlwtjbg /201407/t20140721_47437.htm. (China Internet Network Information Center. The 34th Statistics Report of China Internet Development [R/OL]. [2014-07-26].
[2] 《2013年中国人权事业的进展》白皮书[EB/OL]. [2014-08-02]. (Progress of China's Human Rights in 2013 [EB/EL]. [2014-08-02].
[3] Wu M, Guo J, Zhang C, et al. Social Media Communication Model Research Based on Sina-weibo [C]. In: Proceedings of the 6th International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China. Springer Berlin Heidelberg, 2011: 445-454.
[4] 郑蕾, 李生红. 基于微博网络的信息传播模型[J]. 通信技术, 2012, 45(2): 39-41. (Zheng Lei, Li Shenghong. A Novel Information Diffusion Model Based on Microblog Network [J]. Communications Technology, 2012, 45(2): 39-41.)
[5] Xiong F, Liu Y, Zhang Z, et al. An Information Diffusion Model Based on Retweeting Mechanism for Online Social Media [J]. Physics Letters A, 2012, 376(30-31): 2103-2108.
[6] 田占伟, 隋玚. 基于复杂网络理论的微博信息传播实证分析[J]. 图书情报工作, 2013, 57(8): 42-46. (Tian Zhanwei, Sui Yang. The Empirical Analysis of Micro-blog Information Flow Based on Complex Network Theory [J]. Library and Information Service, 2013, 57(8): 42-46.)
[7] 田盼, 何跃. 基于SOM-GMDH的微博热点话题变化趋势研究[J]. 软科学, 2013, 27(8): 75-79, 109. (Tian Pan, He Yue. Study on the Development Trend of Hot Topics on Micro-blogging Based on SOM-GMDH [J]. Soft Science, 2013, 27(8): 75-79, 109.)
[8] 张赛, 徐恪, 李海涛. 微博类社交网络中信息传播的测量与分析[J]. 西安交通大学学报, 2013, 47(2): 124-130. (Zhang Sai, Xu Ke, Li Haitao. Measurement and Analysis of Information Propagation in Online Social Networks like Microblog [J]. Journal of Xi'an Jiao Tong University, 2013, 47(2): 124-130.)
[9] 兰月新. 突发事件微博舆情扩散规律模型研究[J]. 情报科学, 2013, 31(3): 31-34. (Lan Yuexin. Research on Microblog Opinion Diffusion Model of Emergent Events [J]. Information Science, 2013, 31(3): 31-34.)
[10] Wang H, Li Y, Feng Z, et al. Retweeting Analysis and Prediction in Microblogs: An Epidemic Inspired Approach [J]. China Communications, 2013, 10(3): 13-24.
[11] 付宏, 田丽. 基于微博传播的舆情演进案例研究[J]. 图书情报工作, 2013, 57(15): 34-38, 95. (Fu Hong, Tian Li. The Case Study on the Evolution of Public Opinion Based on MicroBlog-spread [J]. Library and Information Service, 2013, 57(15): 34-38, 95.)
[12] 赵蓉英, 曾宪琴. 微博信息传播的影响因素研究分析[J]. 情报理论与实践, 2014, 37(3): 58-63. (Zhao Rongying, Zeng Xianqin. Analysis of Influencing Factors Micro-blog Information Dissemination [J]. Information Studies: Theory & Application, 2014, 37(3): 58-63.)
[13] 张玥, 孙霄凌, 浦正宁, 等. 微博舆情传播影响因素研究——基于信源特征和信息形式的视角[J]. 情报资料工作, 2014(3): 59-64. (Zhang Yue, Sun Xiaoling, Pu Zhengning, et al. Influencing Factors of Microblog Public Opinion Dissemination: Based on the Perspective of Information Source Characteristic and Information Form [J]. Information and Documentation Services, 2014(3): 59-64.)
[14] 胡晓峰, 贺筱媛, 徐旭林. 大数据时代对建模仿真的挑战与思考——中国科协第81期新观点新学说学术沙龙综述[J]. 中国科学: 信息科学, 2014, 44(5): 676-692. (Hu Xiaofeng, He Xiaoyuan, Xu Xulin. Simulation in the Big Data Era-Review of New Ideas and New Theories in the 81st Academic Salon of China Association for Science and Technology [J]. Scientia Sinica Informationis, 2014, 44(5): 676-692.)
[15] 李姣, 刘泽照. 微博时代政府对网络事件的应急回应[J]. 新闻知识, 2011(9): 45-46. (Li Jiao, Liu Zezhao. Micro-blog Era Government Emergency Response to Network Events [J]. News Research, 2011(9): 45-46.)
[16] 浙江余姚市台风灾害舆情分析[EB/OL]. [2014-08-03]. (Zhejiang Public Opinion Analysis of Typhoon Disasters in Yuyao City [EB/OL]. [2014-08-03]. http://yuqing.people.
[17] 2012年中国互联网舆情分析报告[R/OL]. [2014-07-26]. (2012 China Internet Public Opinion Analysis Report [R/OL]. [2014-07-26]. 1221/c210123-19974822-2.html.)
[18] 2012年3季度网络舆情报告(0.997版) [R/OL]. [2014-07-26]. (The 3rd Quarter of 2012 Network Public Opinion Report (0.997 Edition) [R/OL]. [2014-07-26].
[19] 王慧, 兰月新, 潘樱心. 基于信息异化动力视角的网络衍生舆情成因研究[J]. 现代情报, 2013, 33(7): 59-63, 117. (Wang Hui, Lan Yuexin, Pan Yingxin. Research About Causes of Formation of Public Opinion Derived Network Based on Information Alienation Power [J]. Journal of Modern Information, 2013, 33(7): 59-63,117.)
[20] 宁宣熙, 刘思峰. 管理预测与决策方法[M]. 北京: 科学出版社, 2008: 120-121. (Ning Xuanxi, Liu Sifeng. Management Forecast and Decision-making Methods [M]. Beijing: Science Press, 2008: 120-121.)
[21] 案例库 [EB/OL]. [2014-08-07]. htm. (The Case Base [EB/OL]. [2014-08-07]. http://yq.people.
[22] 广西贺江水污染事件舆情分析[EB/OL]. [2014-08-03]. (Analysis of Guangxi He River Water Pollution Incidents of Public Opinion [EB/OL]. [2014-08-03]. http://yuqing.
[23] 吴怡蓉. 突发公共事件应急处置中的舆论引导——以贺江水污染事件为例[J]. 新闻世界, 2013(12): 66-67. (Wu Yirong. Emergency Disposal of Sudden Public Incidents of Public Opinion Guidance—For He-River Water Pollution Incident as an Example [J]. News World, 2013(12): 66-67.)

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