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[Conference News] Extracting Hidden Behavioral Patterns from Social Network Data

Massive information about human behavior is continuously generated by Web-based services, both public and private. The data include traces of not only individual activities but also collaborative work, and the social networks that can be extracted from these datasets offer a kind of knowledge that’s independent of user awareness.

In a paper presented at the 2013 International Conference on Social Intelligence and Technology (Social 2013), researchers from the Wroclaw University of Technology in Poland describe a data-driven approach to social network analysis that enables various applications of knowledge about human behavior. They illustrate selected models and analytical methods in applications to recommender systems, organizational structure analysis, and social group evolution.

From Data to Human Behaviour” and other papers from Social 2013 are available to both IEEE Computer Society members and paid subscribers via the Computer Society Digital Library.

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