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The Enron email corpus is appealing to researchers because it is a) a large scale email collection from b) a real organization c) over a period of 3.5 years. We contribute to the investigation of the Enron email dataset from a social network analytic perspective. The corpus contains a large amount of information on interaction, communication, knowledge, cognition, resources, tasks and relationships on an individual and group level in Enron. In order to explore and understand how these factors might have impacted the network, its design, culture, and life cycle, we need to extract and analyze this information in an effective and efficient way.

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This work is part of the Dynamics Networks project in CASOS (Center for Computational Analysis of Social and Organizational Systems, http://www.casos.cs.cmu.edu ) at Carnegie Mellon University . This work was supported in part by the Office of Naval Research (ONR), United States Navy Grant No. 9620.1.1140071 on Dynamic Network Analysis under the direction of Rebecca Goolsby. Additional support on measures was provided by the DOD and the NSF. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the National Science Foundation or the U.S. government.

Further Acknowledgement: We thank Corinne Coen (SUNY, Buffalo ) for her advice on this projec and Eduard Hovy (USC, ISI) for pointing us to ISI's work on Enron.