Analysis of Content Popularity in Social Bookmarking Systems

Abstract

The recent advent and wide adoption of Social Bookmarking Systems (SBS) has disrupted the traditional model of online content publishing and consumption. Until recently, the majority of content consumed by people was published as a result of a centralized selection process. Nowadays, the large-scale adoption of the Web 2.0 paradigm has diffused the content selection process to the masses. Modern SBS-based applications permit their users to submit their preferred content, comment on and rate the content of other users and establish social relations with each other. As a result, the evolution of popularity of socially bookmarked content constitutes nowadays an overly complex phenomenon calling for a multi-aspect analysis approach. This chapter attempts to provide a unified treatment of the phenomenon by studying four aspects of popularity of socially bookmarked content: (a) the distributional properties of content consumption, (b) its evolution in time, (c) the correlation between the semantics of online content and its popularity, and (d) the impact of online social networks on the content consumption behavior of individuals. To this end, a case study is presented where the proposed analysis framework is applied to a large dataset collected from Digg, a popular social bookmarking and rating application.