Empirical analysis of web-based user-object bipartite networks

被引：139

作者：

Shang, Ming-Sheng ^{[1
,2
]}

Lue, Linyuan ^{[2
]}

Zhang, Yi-Cheng ^{[1
,2
]}

Zhou, Tao ^{[1
,3
]}

机构：

[1] Univ Elect Sci & Technol China, Web Sci Ctr, Sch Comp Sci & Engn, Chengdu 610054, Peoples R China

[2] Univ Fribourg, Dept Phys, CH-1700 Fribourg, Switzerland

[3] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China

来源：

EPL | 2010年 / 90卷 / 04期

基金：

中国国家自然科学基金; 瑞士国家科学基金会;

关键词：

COMPLEX NETWORKS; RECOMMENDER SYSTEMS; COLLABORATION NETWORKS; GRAPHS; DYNAMICS;

D O I：

10.1209/0295-5075/90/48006

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative similarity, to quantify the diversity of tastes based on the collaborative selection. Accordingly, the correlation between degree and selection diversity is investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem. Copyright (C) EPLA, 2010

引用

页数：6

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