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      The Visualization of Mass Information in Social Network with a Holistic View

      , , , , ,

      Electronic Visualisation and the Arts (EVA 2011) (EVA)

      Electronic Visualisation and the Arts (EVA 2011)

      6 - 8 July 2011

      Information flow, Holistic view, Communication effect, 3-Dimension visualization, Social network

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          In this paper, we propose visualization for mass information in the social network with a holistic view, which focused on representing the effect of user communication. With the Rapid Expansion of social network, it is necessary to provide a holistic view to the users and researchers to understand the effect of information communicated in the network. The social network users will be visualized in 3-dimension space, with 2-dimension graph layouts delivering various characteristic of the network. The layout is mainly based on user’s role in the network, but not the relationship of users in the traditional way. By visualizing the disseminating and stop of information flow among users, we can distinguish users by their effect and contribution in communication among the network. The visualization combines technology, content and expression. We can then study the social network by the performance of the network structure situation and information flow.

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          A simple model of global cascades on random networks.

          The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascades-herein called global cascades-that occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.

            Author and article information

            July 2011
            July 2011
            : 124-131
            Department of Computer Science and

            Technology, Tsinghua University,

            Beijing, P. R. China
            School of Journalism and

            Communication, Tsinghua University,

            Beijing, P. R. China
            Department of Information Art and

            Design, Tsinghua University, Beijing,

            P. R. China
            © Xin Li et al. Published by BCS Learning and Development Ltd. Electronic Visualisation and the Arts (EVA 2011), London, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

            Electronic Visualisation and the Arts (EVA 2011)
            London, UK
            6 - 8 July 2011
            Electronic Workshops in Computing (eWiC)
            Electronic Visualisation and the Arts (EVA 2011)
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page):
            Electronic Workshops in Computing


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