Measurement and Analysis of Online Social Networks

被引:0
|
作者
Mislove, Alan [1 ,2 ]
Marcon, Massimiliano [1 ]
Gummadi, Krishna R. [1 ]
Druschel, Peter [1 ]
Bhattacharjee, Bobby [3 ]
机构
[1] MPI Software Syst, Campus E1 4, D-66123 Saarbrucken, Germany
[2] Rice Univ, Houston, TX 77005 USA
[3] Univ Maryland, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
Social networks; measurement; analysis;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a powerful means of sharing, organizing, and finding content and contacts. The popularity of these sites provides an opportunity to study the characteristics of online social network graphs at large scale. Understanding these graphs is important, both to improve current systems and to design new applications of online social networks. This paper presents a large-scale measurement study and analysis of the structure of multiple online social networks. We examine data gathered from four popular online social networks: Flickr, YouTube, LiveJournal, and Orkut. We crawled the publicly accessible user links on each site, obtaining a large portion of each social network's graph. Our data set contains over 11.3 million users and 328 million links. We believe that this is the first study to examine multiple online social networks at scale. Our results confirm the power-law, small-world, and scale-free properties of online social networks. We observe that the indegree of user nodes tends to match the outdegree; that the networks contain a densely connected core of high-degree nodes; and that this core links small groups of strongly clustered, low-degree nodes at the fringes of the network. Finally, we discuss the implications of these structural properties for the design of social network based systems.
引用
收藏
页码:29 / +
页数:3
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