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As a typical social media in Web 2.0 era, blogs have become more and more important to information diffusion. Different from the traditional news, the information spread on blogs is primarily driven by users and their relations. According to this phenomenon, this paper addresses the novel problem of measuring the influence of social structures on information diffusion. This paper extracts the hidden communities and information diffusion networks on blogs, and proposes a novel quantitative measurement to investigate the influence of social networks structure on diffusion networks. The proposed methods measure the influence by utilizing a simple but effective graph similarity measuring method. The experiments demonstrate the effectiveness of the proposed algorithms and measurements, and discover the correlation between social networks and the diffusion of the ldquointerestrdquo topics, which indicates the necessity of using social structures for information detection and tracking on blogs.
Machine Learning and Cybernetics, 2009 International Conference on (Volume:6 )
Date of Conference: 12-15 July 2009