Please wait a minute...
New Technology of Library and Information Service  2014, Vol. 30 Issue (5): 66-73    DOI: 10.11925/infotech.1003-3513.2014.05.09
INFORMATION ANALYSIS AND RESEARCH Current Issue | Archive | Adv Search |
The Study of Local-world Network Evolution Model Based on Microblog
He Yumei1, Qi Jiayin2, Liu Huili2
1 School of Ecomomics and Management, Tsinghua University, Beijing 100084, China;
2 School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] Through the study of microblog network’s features, a local network evolution model of Sina Microblog is developed in this paper. [Methods] With Sina Microblog entire network data and a typical user’s topological structure, a model is explored based on the theories of public opinion dynamics and complex network. [Results] A framework for microblog users’ behaviors is obtained, a division basis for ordinary users and opinion leaders is got, and the local network evolution model is developed. [Limitations] In this method, the selection of typical user has its limitation, and the analysis of the entire network data has a certain deviation. [Conclusions] Finally, a conclusion can be obtained that the local network evolution model accord with real microblog network topology. The research work of this paper is helpful to know the microblog network structure well.

Key wordsMicroblog      Complex network      Public opinion transmission      Evolution model     
Received: 25 December 2013      Published: 06 June 2014
:  G206  

Cite this article:

He Yumei, Qi Jiayin, Liu Huili. The Study of Local-world Network Evolution Model Based on Microblog. New Technology of Library and Information Service, 2014, 30(5): 66-73.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.05.09     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I5/66

[1] 刘挺, 徐志明, 秦兵, 等.从语言计算到社会计算[J].中国计算机学会通讯, 2011, 7(12): 31-39. (Liu Ting, Xu Zhiming, Qin Bing, et al. From Language Computing to Social Computing [J]. Communications of the China Computer Federation, 2011, 7(12): 31-39.)
[2] 李海峰. 微博对突发事件的影响作用探究[J]. 宁波大学学报: 人文科学版, 2012, 25(1): 124-127. (Li Haifeng. On the Impacts of Micro-Blogs on Emergencies [J]. Journal of Ningbo University: Liberal Arts Edition, 2012, 25(1): 124-127.)
[3] 董立人, 董乐铄. 舆论动力学初探[J]. 华北水利水电学报: 社科版, 2009, 25(2): 24-26. (Dong Liren, Dong Leshuo. Initial Exploration of Opinion Dynamics [J]. Journal of North China Institute of Water Conservancy and Hydroelecric Power: Social Science, 2009, 25(2): 24-26.)
[4] 白林根, 谌志群, 王荣波, 等. 微博关注关系网络K-核结构实证分析[J].现代图书情报技术, 2013(11): 68-74.(Bai Lin'gen, Chen Zhiqun, Wang Rongbo, et al. Empirical Analysis on K-core of Microblog Following Relationaship Network [J]. New Technology of Library and Information Service, 2013(11): 68-74.)
[5] Sznajd-Weron K, Sznajd J.Opinion Evolution in Closed Community[J]. International Journal of Physics C, 2000, 11(6): 1157-1165.
[6] Deffuant G,Neau D, Amblard F,et al. Mixing Beliefs among Interacting Agents[J]. Advance in Complex System, 2000, 3(4): 87-98.
[7] Hegeselmann R, Krause U.Opinion Dynamics Driven by Various Ways of Averaging[J]. Computational Economics, 2005, 25(4): 381-405.
[8] Stauffer D, Sousa A O, Oliveira S M. Generalization to Square Lattice of Sznajd Sociophysics Model [J]. International Journal of Modern Physics C, 2000, 11(6): 1239-1245.
[9] 王茹, 蔡勖. 小世界网络上个体持续度的舆论动力学研究[J]. 复杂系统与复杂科学, 2008, 5(2): 46-50. (Wang Ru, Cai Xu. The Small-world Topology and Individual Persistence Effect in Opinion Dynamics [J]. Complex Systems and Complexity Science, 2008, 5(2): 46-50.)
[10] 刘常昱, 胡晓峰, 罗批, 等. 基于不对称人际影响的舆论涌现模型研究[J]. 系统仿真学报, 2008, 20(4): 990-992, 996. (Liu Changyu, Hu Xiaofeng, Luo Pi, et al. Based on Asymmetric Personal Relatinship Influence[J].Journal of System Simulation, 2008, 20(4): 990-992, 996.)
[11] Fortunato S. On the Consensus Threshold for the Opinion Dynamics of KrauseHegselmann [J]. International Journal of Modern Physics C, 2005, 16(2):259-270.
[12] Barabási A L, Albert R. Emergence of Scaling in Random Networks [J]. Science, 1999, 286(5439): 509-512.
[13] 崔爱香, 傅彦, 尚明生, 等. 复杂网络局部结构的涌现: 共同邻居驱动网络演化 [J]. 物理学报, 2011, 60(3): 809-814. (Cui Aixiang, Fu Yan, Shang Mingsheng, et al. Emergence of Local Stuctures in Complex Network: Common Neigh-borhood Drives the Network Evolution [J]. Acta Physica Sinica, 2011, 60(3): 809-814.)
[14] 安海忠, 于文静. 项目导向型社会的复杂适应系统结构模型研究 [J]. 改革与战略, 2008, 24(11): 77-79. (An Haizhong, Yu Wenjing. On Structural Model of Complex Adaptive Systems for Project-Oriented Society [J]. Reformation & Strategy, 2008, 24(11): 77-79. )
[15] 杜海峰, 悦中山, 李树茁, 等. 基于模块性指标的动态网络社群结构探测方法[J]. 系统工程理论与实践, 2009, 29(3): 162-171. (Du Haifeng, Yue Zhongshan, Li Shuzhuo, et al. Community Structure Detecting Alorithm for Dynamic Networks Based on Modularity [J]. Systems Engineering- Theory & Practice, 2009, 29(3): 162-171. )
[16] 郑雅真. 新浪微博的发展研究[D]. 北京: 北京交通大学, 2010. (Deng Yazhen. Research of Sina Microblog's Development [D]. Beijing: Beijing Jiaotong University, 2010.)
[17] 夏雨禾. 突发事件中的微博舆论: 基于新浪微博的实证研究[J]. 新闻与传播研究, 2011(5): 43-51. (Xia Yuhe. Microblog Opinions on Emergency: an Empirical Study Based on Sina Microblog [J]. Journalism & Communication, 2011(5): 43-51.)
[18] 丁雪峰, 胡勇, 赵文, 等.网络舆论意见领袖特征研究[J]. 四川大学学报: 工程科学版, 2010, 42(2):145-149.(Ding Xuefeng, Hu Yong, Zhao Wen, et al. A Study on the Characters of the Public Opinion Leader in Web BBS [J]. Journal of Sichuan University: Engineering Scinece Edition, 2010, 42(2):145-149.)
[19] 原福永, 冯静, 符茜茜, 等. 一种降低微博僵尸粉影响的方法 [J]. 现代图书情报技术, 2012(5): 70-75.(Yuan Fuyong, Feng Jing, Fu Qianqian, et al. A Method to Reduce the Impact of Zombie Fans in Micro-blog [J]. New Technology of Library and Information Service, 2012(5): 70-75.)
[20] 吕非非, 徐雅斌, 李卓, 等. 面向微博影响力的社交网络特征分析[J]. 计算机应用, 2013, 33(12): 3359-3362, 3418. (Lv Feifei, Xu Yabin, Li Zhuo, et al. Analysis of Charac-teristics of Social Networks in Terms of Microblog Impact[J]. Journal of Computer Applications, 2013, 33(12): 3359-3362, 3418.)
[21] 陈冰鑫, 邱保志. 聚类消息中间件构造技术 [J]. 计算机应用, 2012, 32(5): 1425-1428. (Chen Bingxin, Qiu Baozhi. Construction Technology of Cluster Message-oriented Middleware [J]. Journal of Computer Applications, 2012, 32(5): 1425-1428.)
[22] 郭印, 刘维清. 具有局部无标度特性的小世界网络模型 [J]. 江西理工大学学报, 2012, 33(1): 73-77.(Guo Yin, Liu Weiqing. Model of Small World Network with Local Scale Free Structure [J]. Journal of Jiangxi University of Science and Technology, 2012, 33(1): 73-77.)
[23] 吕丽, 张素娟, 樊锁海. 一个科研合作复杂网络模型的实证研究 [J]. 暨南大学学报: 自然科学与医学版, 2011, 32(5): 462-467. (Lv Li, Zhang Sujuan, Fan Suohai. Research of a Complex Network Model on Scientific Collaboration [J]. Journal of Jinan University: Natural Science & Medicine Edition, 2011, 32(5): 462-467.)
[24] Kwak H, Lee C Y, Park H, et al. What is Twitter, a Social Network or a News Media?[C]. In: Proceedings of the 19th International Conference on World Wide Web(IW3C2), Raleigh, Raleigh NC, USA.2010:591-600.

[1] Chen Wenjie,Wen Yi,Yang Ning. Fuzzy Overlapping Community Detection Algorithm Based on Node Vector Representation[J]. 数据分析与知识发现, 2021, 5(5): 41-50.
[2] Zhang Mengyao, Zhu Guangli, Zhang Shunxiang, Zhang Biao. Grouping Microblog Users of Trending Topics Based on Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(2): 43-49.
[3] Xi Yunjiang, Du Diedie, Liao Xiao, Zhang Xuehong. Analyzing & Clustering Enterprise Microblog Users with Supernetwork[J]. 数据分析与知识发现, 2020, 4(8): 107-118.
[4] Li Tiejun,Yan Duanwu,Yang Xiongfei. Recommending Microblogs Based on Emotion-Weighted Association Rules[J]. 数据分析与知识发现, 2020, 4(4): 27-33.
[5] Li Wenzheng,Gu Yijun,Yan Hongli. Predicting Community Numbers with Network Bayesian Information Criterion[J]. 数据分析与知识发现, 2020, 4(4): 72-82.
[6] Liang Yanping,An Lu,Liu Jing. Topic Resonance of Micro-blogs on Similar Public Health Emergencies[J]. 数据分析与知识发现, 2020, 4(2/3): 122-133.
[7] Xu Yuemei,Liu Yunwen,Cai Lianqiao. Predicitng Retweets of Government Microblogs with Deep-combined Features[J]. 数据分析与知识发现, 2020, 4(2/3): 18-28.
[8] Han Kangkang,Xu Jianmin,Zhang Bin. Recommending Microblogs with User’s Interests and Multidimensional Trust[J]. 数据分析与知识发现, 2020, 4(12): 95-104.
[9] Bocheng Li,Yunqiu Zhang,Kaixi Yang. Extracting Emotion Tags from Comments of Microblog Commodities[J]. 数据分析与知识发现, 2019, 3(9): 115-123.
[10] Lu An,Yanping Liang. Selection of Users’ Behaviors Towards Different Topics of Microblog on Public Health Emergencies[J]. 数据分析与知识发现, 2019, 3(4): 33-41.
[11] Xiang Li,Xiaodong Qian. Research on Impact of Commodity Online Evaluation for Consumption Convergence[J]. 数据分析与知识发现, 2019, 3(3): 102-111.
[12] Jiao Yan,Jing Ma,Kang Fang. Computing Text Semantic Similarity with Syntactic Network of Co-occurrence Distance[J]. 数据分析与知识发现, 2019, 3(12): 93-100.
[13] Wuxuan Jiang,Huixiang Xiong,Jiaxin Ye,Ning An. Creating Dynamic Tags for Social Networking Groups[J]. 数据分析与知识发现, 2019, 3(10): 98-109.
[14] Qian Xiaodong,Li Min. Identifying E-commerce User Types Based on Complex Network Overlapping Community[J]. 数据分析与知识发现, 2018, 2(6): 79-91.
[15] Chen Yunwei,Zhang Ruihong. Comparing on Community Detection Algorithms for Information Mining[J]. 数据分析与知识发现, 2018, 2(10): 84-94.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn