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The International Conference on Advances in Social Network Analysis and Mining (ASONAM 2011)

http://asonam.im.nuk.edu.tw/

July 25-27, 2011 - Kaohsiung City, Taiwan

The study of social networks originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding.

The international conference on Advances in Social Network Analysis and Mining (ASONAM 2011) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. ASONAM 2011 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoretical works on social network analysis and mining along with their application to real life situations.

General areas of interest to ASONAM 2011 include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

More specialized topics within ASONAM include, but are not limited to:

        Anomaly detection in social network evolution Application of social network analysis
        Application of social network mining
        Communities discovery and analysis in large scale online social networks
        Communities discovery and analysis in large scale offline social networks
        Connection between biological similarities and social network formulation
        Contextual social network analysis
        Contextual social network mining
        Crime data mining and network analysis
        Cyber anthropology
        Dark Web
        Data protection inside communities
        Detection of communities by document analysis
        Dynamics and evolution patterns of social networks
        Economical impact of social network discovery
        Evolution of patterns in the Web
        Evolution of communities in the Web
        Evolution of communities in organizations
        Geography of social networks
        Impact of social networks on recommendations systems
        Information acquisition and establishment of social relations
        Influence of cultural aspects on the formation of communities
        Knowledge networks
        Large-scale graph algorithms for social network analysis
        Misbehavior detection in communities
        Migration between communities
        Multi-agent based social network modeling and analysis
        Open source intelligence
        Pattern presentation for end-users and experts
        Personalization for search and for social interaction
        Preparing data for Web mining
        Political impact of social network discovery
        Privacy, security and civil liberty issues
        Recommendations for product purchase, information acquisition and establishment of social relations
        Recommendation networks
        Scalability of social networks
        Scalability of Search algorithms on social networks
        Social and cultural anthropology
        Social geography
        Social psychology of information diffusion
        Temporal analysis on social networks topologies
        Visual representation of dynamic social networks
        Web mining algorithms
        Web communities


Instructions for Authors
Papers reporting original and unpublished research results pertaining to the above topics are solicited.

Full paper submission deadline is March 1, 2011. These papers will follow an academic review process. Full paper manuscripts must be in English with a maximum length of 8 pages (using the IEEE two- column template).

Submissions should include the title, author(s), affiliation(s), e-mail address(es), tel/fax numbers, abstract, and postal address(es) on the first page. Papers should be submitted to the conference Web site: asonam2011.im.nuk.edu.tw. If Web submission is not possible, manuscripts should be sent as an attachment via email to [log in to unmask] by March 1, 2011. The attachment must be in PDF or Word .doc format.

Papers will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation. Authors should certify that their papers represent substantially new previously unpublished work. Paper submission implies that the intent is for one of the authors to present the paper if accepted and that at least one of the authors register for a full conference fee.

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Asst. Prof. Tansel Özyer
Department of Computer Engineering
TOBB ETU, Ankara Turkey
http://ozyer.etu.edu.tr
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