IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v11y2005i3d10.1007_s10588-005-5379-y.html
   My bibliography  Save this article

Structure in the Enron Email Dataset

Author

Listed:
  • P. S. Keila

    (Queen's University)

  • D. B. Skillicorn

    (Queen's University)

Abstract

We investigate the structures present in the Enron email dataset using singular value decomposition and semidiscrete decomposition. Using word frequency profiles, we show that messages fall into two distinct groups, whose extrema are characterized by short messages and rare words versus long messages and common words. It is surprising that length of message and word use pattern should be related in this way. We also investigate relationships among individuals based on their patterns of word use in email. We show that word use is correlated to function within the organization, as expected. Lastly, we show that relative changes to individuals' word usage over time can be used to identify key players in major company events.

Suggested Citation

  • P. S. Keila & D. B. Skillicorn, 2005. "Structure in the Enron Email Dataset," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 183-199, October.
    • Handle: RePEc:spr:comaot:v:11:y:2005:i:3:d:10.1007_s10588-005-5379-y
    DOI: 10.1007/s10588-005-5379-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-005-5379-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-005-5379-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simon, Adam F. & Xenos, Michael, 2004. "Dimensional Reduction of Word-Frequency Data as a Substitute for Intersubjective Content Analysis," Political Analysis, Cambridge University Press, vol. 12(1), pages 63-75, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael W. Berry & Murray Browne, 2005. "Email Surveillance Using Non-negative Matrix Factorization," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 249-264, October.
    2. Jana Diesner & Terrill L. Frantz & Kathleen M. Carley, 2005. "Communication Networks from the Enron Email Corpus “It's Always About the People. Enron is no Different”," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 201-228, October.
    3. Alastair Irons & Harjinder Singh Lallie, 2014. "Digital Forensics to Intelligent Forensics," Future Internet, MDPI, vol. 6(3), pages 1-13, September.
    4. Hady W. Lauw & Ee-Peng Lim & HweeHwa Pang & Teck-Tim Tan, 2005. "Social Network Discovery by Mining Spatio-Temporal Events," Computational and Mathematical Organization Theory, Springer, vol. 11(2), pages 97-118, July.
    5. Anurat Chapanond & Mukkai S. Krishnamoorthy & Bülent Yener, 2005. "Graph Theoretic and Spectral Analysis of Enron Email Data," Computational and Mathematical Organization Theory, Springer, vol. 11(3), pages 265-281, October.
    6. Sriranga Suprabhath Koduru & Venkata Siva Prasad Machina & Sreedhar Madichetty, 2023. "Cyber Attacks in Cyber-Physical Microgrid Systems: A Comprehensive Review," Energies, MDPI, vol. 16(12), pages 1-36, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Justin Wedeking, 2010. "Supreme Court Litigants and Strategic Framing," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 617-631, July.
    2. Daniel J. Hopkins & Gary King, 2010. "A Method of Automated Nonparametric Content Analysis for Social Science," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 229-247, January.
    3. Lauren Guggenheim & S. Mo Jang & Soo Young Bae & W. Russell Neuman, 2015. "The Dynamics of Issue Frame Competition in Traditional and Social Media," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 207-224, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:comaot:v:11:y:2005:i:3:d:10.1007_s10588-005-5379-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.