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Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on

Date 25-27 July 2011

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Displaying Results 1 - 25 of 129
  • [Front cover]

    Publication Year: 2011, Page(s): C1
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  • [Title page i]

    Publication Year: 2011, Page(s): i
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  • [Title page iii]

    Publication Year: 2011, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2011, Page(s): iv
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  • Table of contents

    Publication Year: 2011, Page(s):v - xiv
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  • Message from the General Chairs

    Publication Year: 2011, Page(s):xv - xvi
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  • Message from the Program Chairs

    Publication Year: 2011, Page(s):xvii - xviii
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  • Conference sponsors

    Publication Year: 2011, Page(s):xix - xxi
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  • Conference Committee

    Publication Year: 2011, Page(s):xxii - xxiii
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  • Program Committee

    Publication Year: 2011, Page(s):xxiv - xxvii
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  • External Reviewers

    Publication Year: 2011, Page(s): xxviii
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  • Invited Keynote Speakers

    Publication Year: 2011, Page(s): xxix
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (115 KB) | HTML iconHTML

    Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • The ML-Model for Multi-layer Social Networks

    Publication Year: 2011, Page(s):5 - 12
    Cited by:  Papers (20)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2948 KB) | HTML iconHTML

    In this paper we introduce a new model to represent an interconnected network of networks. This model is fundamental to reason about the real organization of on-line social networks, where users belong to and interact on different networks at the same time. In addition we extend traditional SNA measures to deal with this multiplicity of networks and we apply the model to a real dataset extracted f... View full abstract»

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  • Tag-based User Topic Discovery Using Twitter Lists

    Publication Year: 2011, Page(s):13 - 20
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB) | HTML iconHTML

    In this paper, we address the problem of tagging users in Twitter, one of the most popular micro-blogging services. There are growing needs to get useful information from Twitter, because an enormous amount of information is transmitted in real time. Twitter users, who play an important role as information sources, typically transmit information about some particular topics which they are interest... View full abstract»

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  • Content-based Modeling and Prediction of Information Dissemination

    Publication Year: 2011, Page(s):21 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (433 KB) | HTML iconHTML

    Social and communication networks across the world generate vast amounts of graph-like data each day. The modeling and prediction of how these communication structures evolve can be highly useful for many applications. Previous research in this area has focused largely on using past graph structure to predict future links. However, a useful observation is that many graph datasets have additional i... View full abstract»

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  • SCENE: Structural Conversation Evolution NEtwork

    Publication Year: 2011, Page(s):29 - 36
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2723 KB) | HTML iconHTML

    It's not just what you say, but it is how you say it. To date, the majority of the Instant Message (IM) analysis and research has focused on the content of the conversation. The main research question has been, `what do people talk about?' focusing on topic extraction and topic modeling. While content is clearly critical for many real-world applications, we have largely ignored identifying `how' p... View full abstract»

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  • Efficient Search in Networks Using Conductance

    Publication Year: 2011, Page(s):37 - 44
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (229 KB) | HTML iconHTML

    Decentralized search in networks is an important algorithmic problem in the study of complex networks and social networks analysis. It has a large number of practical applications, from shortest paths search in social network relationship, web pages search in WWW to querying files in peer-to-peer file sharing networks and so on. In this paper, we explore this problem from a perspective of communit... View full abstract»

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  • A Semantic and Multidisciplinary Model for Professional and Social Networks Analysis

    Publication Year: 2011, Page(s):45 - 52
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (534 KB) | HTML iconHTML

    By bridge-building between the classical models of social networks analysis, ontologies engineering and physics, our work defines a multidisciplinary model of professional social networks analysis, dedicated to human and social capital management in enterprises and institutions. We introduce a semantic process of social graphs static and dynamic analysis, based on the enterprise content and produc... View full abstract»

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  • Visualizing Bibliographic Databases as Graphs and Mining Potential Research Synergies

    Publication Year: 2011, Page(s):53 - 60
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1292 KB) | HTML iconHTML

    Bibliographic databases are a prosperous field for data mining research and social network analysis. They contain rich information, which can be analyzed across different dimensions(e.g., author, year, venue, topic) and can be exploited in multiple ways. The representation and visualization of bibliographic databases as graphs and the application of data mining techniques can help us uncover inter... View full abstract»

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  • Evolutionary Clustering and Analysis of Bibliographic Networks

    Publication Year: 2011, Page(s):63 - 70
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (870 KB) | HTML iconHTML

    In this paper, we study the problem of evolutionary clustering of multi-typed objects in a heterogeneous bibliographic network. The traditional methods of homogeneous clustering methods do not result in a good typed-clustering. The design of heterogeneous methods for clustering can help us better understand the evolution of each of the types apart from the evolution of the network as a whole. In f... View full abstract»

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  • Detecting Link Communities in Massive Networks

    Publication Year: 2011, Page(s):71 - 78
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (891 KB) | HTML iconHTML

    Most of the existing literature which has entirely focused on clustering nodes in large-scale networks. To discover multi-scale overlapping communities quickly, we propose a highly efficient multi-resolution link community detection algorithm to detect the link communities in massive networks based on the idea of edge labeling. First, we will get the node partition of the network based on a new mu... View full abstract»

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  • A Random Network Ensemble Model Based Generalized Network Community Mining Algorithm

    Publication Year: 2011, Page(s):79 - 86
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (488 KB) | HTML iconHTML

    The ability to discover community structures from explorative networks is useful for many applications. Most of the existing methods with regard to community mining are specifically designed for assortative networks, and some of them could be applied to address disassortative networks by means of intentionally modifying the objectives to be optimized. However, the types of the explorative networks... View full abstract»

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  • Evaluating Cooperation in Communities with the k-Core Structure

    Publication Year: 2011, Page(s):87 - 93
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (232 KB) | HTML iconHTML

    Community sub graphs are characterized by dense connections or interactions among its nodes. Community detection and evaluation is an important task in graph mining. A variety of measures have been proposed to evaluate the quality of such communities. In this paper, we evaluate communities based on the k-core concept, as means of evaluating their collaborative nature - a property not captured by t... View full abstract»

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  • Modeling Bipartite Graphs Using Hierarchical Structures

    Publication Year: 2011, Page(s):94 - 101
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (392 KB) | HTML iconHTML

    Bipartite networks are often used to capture the relationships between different classes of objects. To model the structure of bipartite networks, we propose a new hierarchical model based on a hierarchical random graph model originally designed for one-mode networks. The new model can better preserve the network fidelity as well as the assortative and disassortative structures of bipartite networ... View full abstract»

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  • Partitioning Breaks Communities

    Publication Year: 2011, Page(s):102 - 109
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (302 KB) | HTML iconHTML

    Considering a clique as a conservative definition of community structure, we examine how graph partitioning algorithms interact with cliques. Many popular community-finding algorithms partition the entire graph into non-overlapping communities. We show that on a wide range of empirical networks, from different domains, significant numbers of cliques are split across separate partitions, as produce... View full abstract»

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