图书情报工作

图书情报工作 >

2013 , Vol. 57 >Issue 14: 97 - 104,22

DOI: https://doi.org/10.7536/j.issn.0252-3116.2013.14.017

情报研究

兴趣社交网站中意见领袖识别的研究——以“点点网”为例

  • 王娟 ,
  • 曹树金 ,
  • 姜灵敏 ,
  • 唐宝珍
展开
  • 1. 广东外语外贸大学思科信息学院;
    2. 中山大学资讯管理学院
王娟,广东外语外贸大学思科信息学院讲师,中山大学资讯管理学院博士研究生,E-mail:misisipiwj@126.com;曹树金,中山大学资讯管理学院教授;姜灵敏,广东外语外贸大学思科信息学院教授;唐宝珍,广东外语外贸大学思科信息学院讲师。

收稿日期: 2013-06-24

  网络出版日期: 2013-07-20

基金资助

本文系2012年度国家社会科学基金重大项目"基于特定领域的网络资源知识组织与导航机制研究"(项目编号:12&ZD222)和2012年度教育部人文社会科学研究青年基金项目"面向轻博客热点话题情感倾向性分析的研究"(项目编号:12YJC870023)研究成果之一。

收起

Research on the Recognition of Opinion Leaders in the Interest Community：A Case Study of diandian. com

  • Wang Juan ,
  • Cao Shujin ,
  • Jiang Lingmin ,
  • Tang Baozhen
Expand
  • 1 Cisco School of Informatics, Guangdong University of Foreign Studies, Guangzhou Guangdong 510420;
    2 School of Information Management, Sun Yat-Sen University, Guangzhou Guangdong 510275

Received date: 2013-06-24

  Online published: 2013-07-20

Fold

摘要

以国内最大的轻博客网站——点点网为研究对象,根据点点网用户间兴趣关系进行社区划分,通过统计兴趣社区的拓扑特性,发现其都具有小世界和无标度特性,说明有少数用户在信息传播中起着至关重要的作用。之后利用节点中心性测量方法进行意见领袖的识别,分析4个已有的中心性指标——连接度、中介度、接近度和核数在点点网意见领袖识别中的不足,构建新的意见领袖识别指标,并通过实验证实该指标具有更高的准确性。

关键词： 意见领袖; 兴趣图谱; 在线社会网络; 轻博客; 社会网络分析

本文引用格式

王娟 , 曹树金 , 姜灵敏 , 唐宝珍 . 兴趣社交网站中意见领袖识别的研究——以“点点网”为例[J]. 图书情报工作, 2013 , 57(14) : 97 -104,22 . DOI: 10.7536/j.issn.0252-3116.2013.14.017

Abstract

This paper takes diandian.com as the study object. It partitions users of diandian.com into five interest communities according to their similar interest relation, and analyzes their topology properties to find that each of them has a small world and scale free characteristics. The result shows that a few users play a crucial role in the process of information dissemination. Then, it recognizes opinion leaders in the interest community with the measurement method of complex network centrality. Then this paper analyzes four centrality indicators which include node degree, betweenness degree, closeness degree and k-core, and finds some problems in the process of recognizing opinion leaders by them. Finally, it proposes a new recognition indicator, and confirms its higher accuracy through an experiment.

Key words： opinion leader; interest graph; online social network; light blogging; social network analysis

参考文献

[1] Lazarsfeld F, Berelson B, Gaudet H,et al. The people's choice[M]. New York:Columbia University Press, 1948.
[2] 高兴. 最新历史版本:兴趣社交网络的崛起[EB/OL].[2013-02-22]. http://www.techcn.com.cn/index.php?edition-view-182991-1.html.
[3] 果子. 影子大亨Tumblr的成功之道 [EB/OL]. [2013-02-21]. http://www.36kr.com/p/201458.html?ref=weixin0222m.
[4] 罗晓光,溪璐路. 基于社会网络分析方法的顾客口碑意见领袖研究[J]. 管理评论, 2012, 24(1):75-81.
[5] 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.
[6] 丁汉青, 王亚萍. SNS网络空间中"意见领袖"特征之分析———以豆瓣网为例[J]. 新闻与传播研究, 2010(3):83-91.
[7] 王君泽, 王雅蕾, 禹航,等. 微博客意见领袖识别模型研究[J]. 新闻与传播研究, 2011(6):81-88.
[8] Watts D J, Strogatz S H. Collective dynamics of small world networks[J]. Nature, 1998, 393(6684):440-442.
[9] Barabási A L, Albert R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439):509- 512.
[10] Java A, Song Xiaodan, Finin T, et al. Why we Twitter:Understanding micro-blogging usage and communities[C]//Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis. New York:ACM Press,2007:56-65.
[11] Mislove A, Marcon M, Gummadi K P. Measurement and analysis of online social networks[C]//Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement. New York:ACM Press, 2007:29-42.
[12] Fu Feng, Liu Lianghuan, Wang Long. Empirical analysis of online social networks in the age of Web 2.0[J]. Physica A, 2008,387(2):675-684.
[13] Wilson C, Boe B, Sala A, et a1. User interactions in social networks and their implications[C]//Proceedings of the 4th ACM European Conference on Computer Systems. New York:ACM Press, 2009:205-218.
[14] Dunbar R I M. Coevolution of neocortical size, group size and language in humans[J]. Behavioral and Brain Sciences, 1993,16(4):681-735.
[15] Rogers E M. Diffusion of innovations(5th Ed)[M]. New York:Free Press, 2003.
[16] Lyons B, Henderson K. Opinion leadership in a computer-mediated environment[J]. Journal of Consumer Behavior, 2005,4(5):319-329.
[17] Childers T L. Measurement of opinion leadership[J]. Journal of Marketing Research, 1986, 23(2):184-188.
[18] Wasserman S, Faust K. Social network analysis:Methods and applications[M]. Cambridge:Cambridge University Press, 1994.
[19] Blondel V D, Guillaume J L, Lambiottel R, et al. Fast unfolding of communities in large networks[J]. Journal of Statistical Mechanics :Theory and Experiment, 2008(10):10008-10019.
[20] Radicchi F, Castellano C, Cecconi F, et al. Defining and identifying communities in networks[J]. Proceedings of the National Academy of the Sciences of the United States of America, 2004, 101(9):2658-2663.
[21] Albert R, Barabasi A L. Statistical mechanics of complex networks[J]. Reviews of Modern Physics, 2002, 74(1):47-97.
[22] van der Merwe R, van Heerden G. Finding and utilizing opinion leaders:Social networks and the power of relationships[J]. South African Journal of Business Management, 2009,40(3):65-75.
[23] Callaway D S, Newman M E J, Strogatz S H, et al. Network robustness and fragility:Percolation on random graphs[J]. Physics Review Letters, 2000,85(25):5468-5471.
[24] Freeman L.C. A set of measures of centrality based upon betweenness[J]. Sociometry, 1977,40(1):35-41.
[25] 陈静, 孙林夫. 复杂网络中节点重要度评估[J]. 西南交通大学学报, 2009,44(3):426-429.
[26] Kitsak M, Gallos L K, Havlin S, et al. Identifying influential spreaders in complex networks [J]. Nature Physics, 2010, 6(11):888-893.
[27] 安世虎,都艺兵,曲吉林. 节点集重要性测度[J].中国管理科学, 2006,14(1):106-111.
[28] Bavelas A. A mathematical model for group structures[J]. Human Organization,1948,7(3):16-30.
[29] Tomasz L. Size and connectivity of the k-core of a random graph[J]. Discrete Mathematics, 1991,91(1):61-68.
[30] Lancaster F W, Fayen E G. Information retrieval on-line los angeles[M].Los Angeles:Melville Publishing Co, 1973.

Options
文章导航

/

〈 〉