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

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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Reda Alhajj, University of Calgary, Alberta, Canada

Associate Editors:

George Barnett, University of California at Davis, USA
Rosa M. Benito, Universidad Politécnica de Madrid, Spain
James Caverlee, Texas A&M University, USA
Jana Diesner, University of Illinois at Urbana-Champaign, USA
Martin Ester, Simon Fraser University, Canada
Uwe Glässer, Simon Fraser University, British Columbia, Canada
Tansel Özyer, TOBB University of Economics and Technology, Turkey
Ioannis Panagis, University of Copenhagen, Denmark
Jon Rokne, University of Calgary, Canada
VS Subrahmanian, University of Maryland, College Park, USA
Jie Tang, Tsinghua University, China
Christophe Thovex, University of Nantes, France
Özgür Ulusoy, Bilkent University, Turkey
Roger M. Whitaker, Cardiff University, UK
Rafael Wittek, University of Groningen, The Netherlands

Editorial Board:

Nitin Agarwal, University of Arkansas at Little Rock, USA
Harith Alani, The Open University, United Kingdom
Martin Atzmueller, University of Kassel, Germany
Vladimir Batagelj, University of Ljubljana, Slovenia
Nitesh Chawla, University of Notre Dame, USA
Kathleen M. Carley, Carnegie Mellon University, Pittsburgh, USA
Alfredo Cuzzocrea, University of Trieste, Italy
Hasan Davulcu, University of Arizona, USA
Ying Ding Indiana University, Bloomington, USA
Derek Doran, Wright State University, USA
Sumeet Dua, Louisiana Tech University, Ruston, USA
Artur Dubrawski, Carnegie Mellon University, Pittsburgh, USA
Linton C. Freeman, University of California, Irvine, USA
Shang Gao, Jilin University, China
Philippe J. Giabbanelli, Northern Illinois University, USA
Jun Huan, University of Kansas, USA
Henric Johnson, Blekinge Institute of Technology, Sweden
Panagiotis Karampelas, Hellenic American University, Athens, Greece
Mehmet Kaya, Firat University, Turkey
Siddharth Kaza, Towson University, Maryland, USA
Przemyslaw Kazienko, Wroclaw University of Technology, Poland
Suheil Khoury, American University of Sharjah, United Arab Emirates
Ralf Klamma, RWTH Aachen University, Germany
Matthieu Latapy, LIP6-CNRS et Université Pierre et Marie Curie, France
Ee-Peng Lim, Singapore Management University, Singapore
Shou-De Lin, National Taiwan University, Taiwan
Huan Liu, Arizona State University, Tempe, USA
Zongmin Ma, Northeastern University, China
Kishan G. Mehrotra, Syracus Universitiy, USA
Katina Michael, University of Wollongong, Australia
Rokia Missaoui, Université du Québec en Outaouais (UQO), Canada
Philippa Pattison, University of Melbourne, Australia
Hamid R. Rabiee, Sharif University of Technology, Iran
Giancarlo Ragozini, University of Naples Federico II, Italy
John Scott, University of Plymouth, UK
Jaideep Srivastava, University of Minnesota, USA
Frans N. Stokman, University of Groningen, The Netherlands
Dimitris Spiliotopoulos, Foundation for Research and Technology, Greece
Andrea Tagarelli, University of Calabria, Italy
Jie Tang, Tsinghua University, China
I-Hsien Ting, National University of Kaohsiung, Taiwan
Hanghang Tong, Arizona State University, USA
Sho Tsugawa, University of Tsukuba, Japan
William A. Wallace, Rensselaer Polytechnic Institute, USA
Ingmar Weber, Qatar Computing Research Institute, Qatar
Barry Wellman, University of Toronto, Canada
Uffe Kock Wiil, University of Southern Denmark, Denmark
Bin Wu, Beijing University of Posts and Telecommunications, China
Xintao Wu, University of Arkansas, USA
Guandong Xu, University of Technology Sydney, Australia
Christopher C. Yang, Drexel University, USA
Yuan-Chih Yu, Chinese Culture University, China
Mohammed Zaki, Rensselaer Polytechnic Institute, USA
Daniel Zeng, University of Arizona, USA
Xingquan (Hill) Zhu, University of Technology Sydney, Australia
Katharina A. Zweig, Technical University Kaiserslautern, Germany

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For authors and editors

  • Aims and Scope

    Aims and Scope


    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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