Improved Data Extraction

To meet the Army's need for rapid and accurate analysis of unformatted data in order to support various operations, CMU is developing a set of text and data analysis tools for moving from raw text to network analytic metrics. Techniques from dynamic network analysis (DNA) will be used for the collection, analysis, understanding and prediction of dynamic relations (such as who talks to whom and who knows what) and the impact of such dynamics on individual and group behavior. Computational techniques, such as machine learning and artificial intelligence, will be combined with traditional graph and social network theory, and empirical research on human behavior, groups, organizations, and societies to develop and test tools for data extraction and assessment.

Presentations

Kas, Miray, Wachs, Matthew, Carley, L. Richard, & Carley, Kathleen M. (2012). Incremental Centrality Computations for Dynamic Social Networks. Paper presented at the XXXII International Sunbelt Social Network Conference, Redondo Beach, CA, March 12-18, 2012.
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Joseph, Kenneth & Carley, Kathleen M. (2012). Quantifying Meaning in Interaction on Different Communication Media. Paper presented at the XXXII International Sunbelt Social Network Conference, Redondo Beach, CA, March 12-18, 2012.
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Pfeffer, Jürgen & Carley, Kathleen M. (2012). Using k-centralities to approximate centrality measures in large networks. Paper presented at the XXXII International Sunbelt Social Network Conference, Redondo Beach, CA, March 12-18, 2012.
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