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Social network analysis increasingly bridges the discovery of
patterns in diverse areas of study as more data becomes available
and complex. Yet the construction of huge networks from large data
often requires entirely different approaches for analysis
including; graph theory, statistics, machine learning and data
mining. This work covers frontier studies on social network
analysis and mining from different perspectives such as social
network sites, financial data, e-mails, forums, academic research
funds, XML technology, blog content, community detection and clique
finding, prediction of user's- behavior, privacy in social network
analysis, mobility from spatio-temporal point of view, agent
technology and political parties in parliament. These topics will
be of interest to researchers and practitioners from different
disciplines including, but not limited to, social sciences and
engineering.
Social network analysis increasingly bridges the discovery of
patterns in diverse areas of study as more data becomes available
and complex. Yet the construction of huge networks from large data
often requires entirely different approaches for analysis
including; graph theory, statistics, machine learning and data
mining. This work covers frontier studies on social network
analysis and mining from different perspectives such as social
network sites, financial data, e-mails, forums, academic research
funds, XML technology, blog content, community detection and clique
finding, prediction of user's- behavior, privacy in social network
analysis, mobility from spatio-temporal point of view, agent
technology and political parties in parliament. These topics will
be of interest to researchers and practitioners from different
disciplines including, but not limited to, social sciences and
engineering.
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