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Computer Science - Database Management & Information Retrieval | Social Network Analysis and Mining - incl. option to publish open access

Social Network Analysis and Mining

Social Network Analysis and Mining

Editor-in-Chief: Reda Alhajj

ISSN: 1869-5450 (print version)
ISSN: 1869-5469 (electronic version)

Journal no. 13278

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Social Network Analysis and Mining (SNAM) is a multidisciplinary journal serving researchers and practitioners in academia and industry. It is the main venue for a wide range of researchers and readers from computer science, network science, social sciences, mathematical sciences, medical and biological sciences, financial, management and political sciences. We solicit experimental and theoretical work on social network analysis and mining using a wide range of techniques from social sciences, mathematics, statistics, physics, network science and computer science.

Related subjects » Applications - Complexity - Database Management & Information Retrieval - Political Science - Statistics

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SCOPUS, INSPEC, Google Scholar, DBLP, Emerging Sources Citation Index, OCLC, SCImago, Summon by ProQuest

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  • Aims and Scope

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    Social Network Analysis and Mining (SNAM) is a multidisciplinary journal serving researchers and practitioners in academia and industry. It is the main venue for a wide range of researchers and readers from computer science, network science, social sciences, mathematical sciences, medical and biological sciences, financial, management and political sciences. We solicit experimental and theoretical work on social network analysis and mining using a wide range of techniques from social sciences, mathematics, statistics, physics, network science and computer science.

    The main areas covered by SNAM include:

    (1) data mining advances on the discovery and analysis of communities, personalization for solitary activities (e.g. search) and social activities (e.g. discovery of potential friends), the analysis of user behavior in open forums (e.g. conventional sites, blogs and forums) and in commercial platforms (e.g. e-auctions), and the associated security and privacy-preservation challenges;

    (2) social network modeling, construction of scalable and customizable social network infrastructure, identification and discovery of complex, dynamics, growth, and evolution patterns using machine learning and data mining approaches or multi-agent based simulation;

    (3) social network analysis and mining for open source intelligence and homeland security. Papers should elaborate on data mining and machine learning or related methods, issues associated to data preparation and pattern interpretation, both for conventional data (usage logs, query logs, document collections) and for multimedia data (pictures and their annotations, multi-channel usage data).

    Topics include but are not limited to:

    Applications of social network in business engineering, scientific and medical domains, homeland security, terrorism and criminology, fraud detection, public sector, politics, and case studies
    Anomaly and outlier detection in social networks
    Behavior and identity detection and monitoring
    Community discovery in large-scale and complex social networks
    Contextual social network analysis
    Data models and query models for social networks and social media
    Data preparation for social network analysis and mining
    Data protection inside communities
    Dynamics and evolution patterns of social networks, trend prediction
    Evolution of communities in the Web Information acquisition and establishment of social relations
    Large-scale graph algorithms
    Link and node prediction in social networks
    Misbehaviour detection in communities
    Mobile and stream data analysis for social network applications
    Multi-agent based social network modeling and analysis
    Multidisciplinary applications of social network analysis
    Network integration and conflict resolution
    Online social networking and human computer interaction
    Pattern presentation for end-users and experts
    Personalization for search and for social interaction
    Recommendations for e-commerce and business applications
    Recommendation networks
    Search algorithms on social networks
    Security and privacy in social networks
    Social media monitoring and analysis
    Spatio-temporal aspects in social networks and social media
    Tools and infrastructures for social networking platforms Web 2.0 and Web communities

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