Empirical analysis of web-based user-object bipartite networks

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Published 17 June 2010 Europhysics Letters Association
, , Citation Ming-Sheng Shang et al 2010 EPL 90 48006 DOI 10.1209/0295-5075/90/48006

0295-5075/90/4/48006

Abstract

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.

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10.1209/0295-5075/90/48006