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New Technology of Library and Information Service  2011, Vol. 27 Issue (2): 69-75    DOI: 10.11925/infotech.1003-3513.2011.02.11
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Analysis of Micro-blogging User Character and Motivation ——Take Micro-blogging of Hexun.com as an Example
Zhao Wenbing, Zhu Qinghua, Wu Kewen, Huang Qi
Department of Information Management, Nanjing University, Nanjing 210093,China
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Abstract  

Using metrological methods, this paper analyzes data crawled from micro-blogging of Hexun.com and also uses Pajek to view the social network structure of Hexun micro-blogging. The result shows that, the characters of micro-blogging users have favorable statistic characteristics, and the regional disparities between micro-blogging users are quite remarkable. Moreover, two kinds of micro-blogging users account for almost 90% of the total users. This paper is helpful for other researchers to study micro-blogging users behavior.
Key words： Micro-blogging      User character      User motivation      Social network analysis      Power-law distribution     
Received: 10 December 2010      Published: 25 March 2011
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Cite this article:

Zhao Wenbing, Zhu Qinghua, Wu Kewen, Huang Qi. Analysis of Micro-blogging User Character and Motivation ——Take Micro-blogging of Hexun.com as an Example. New Technology of Library and Information Service, 2011, 27(2): 69-75.

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http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2011.02.11     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2011/V27/I2/69


[1] 微博客-维基百科 . . http://zh.wikipedia.org/zh-cn/%E5%BE%AE%E5%8D%9A%E5%AE%A2.

[2] 微博_百度百科 . .http://baike.baidu.com/view/1567099.htm.

[3] Broder A, Kumar R, Maghoul F, et al. Graph Structure in the Web
[J].Computer Networks,2000,33(1-6): 309-320.

[4] Nardi B A, Schiano D J, Gumbrecht M, et al. Why We Blog
[J].Communications of the ACM, 2004,47(12): 41-46.

[5] Honeycutt C, Herring S C. Beyond Microblogging: Conversation and Collaboration via Twitter . In: Proceedings of the 42nd Hawaii International Conference on System Sciences.2009:1-10.

[6] Java A, Song X, Finin T, et al. Why We Twitter: Understanding Micro-blogging Usage and Communities . In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, University of Maryland, Baltimore County. ACM Press, 2007

[7] Naaman M, Boase J, Lai C H. Is It Really About Me?:Message Content in Social Awareness Streams . In: Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, New York.2010: 189-192.

[8] 黄朔. 媒介融合视域中微博多级传播模式探究
[J]. 东南传播 ,2010(6):99-101.

[9] 卢金珠. 微博客传播特性及盈利模式分析
[J]. 现代传播 ,2010(4):127-130.

[10] 王树义,王鑫. 基于微博客Twitter的企业竞争情报搜集
[J]. 情报学报 ,2010,29(3):545-552.

[11] 崔争艳. 基于语义的微博短信息分类
[J]. 现代计算机:专业版 ,2010(8):18-20.

[12] 王晓光.微博客用户行为特征与关系特征实证分析——以“新浪微博”为例
[J]. 图书情报工作 ,2010,54(14):66-70.

[13] 夏雨禾. 微博互动的结构与机制——基于对新浪微博的实证研究
[J]. 新闻与传播研究 ,2010(4):60-69.

[14] Barabasi A L, Albert R. Emergence of Scaling in Random Networks
[J].Science, 1999,286(5439): 509-512.
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