Research Article

Using rhythms of relationships to understand e-mail archives

  1. Adam Perer1,
  2. Ben Shneiderman1,
  3. Douglas W. Oard2

Article first published online: 2 OCT 2006

DOI: 10.1002/asi.20387

Issue

Journal of the American Society for Information Science and Technology

Journal of the American Society for Information Science and Technology

Volume 57, Issue 14, pages 1936–1948, December 2006

Additional Information

How to Cite

Perer, A., Shneiderman, B. and Oard, D. W. (2006), Using rhythms of relationships to understand e-mail archives. Journal of the American Society for Information Science and Technology, 57: 1936–1948. doi: 10.1002/asi.20387

Author Information

  1. 1

    Human–Computer Interaction Lab, Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, College Park, MD 20742

  2. 2

    Human–Computer Interaction Lab, Institute for Advanced Computer Studies and College of Information Studies, University of Maryland, College Park, MD 20742

Publication History

  1. Issue published online: 10 NOV 2006
  2. Article first published online: 2 OCT 2006
  3. Manuscript Accepted: 1 DEC 2005
  4. Manuscript Revised: 29 NOV 2005
  5. Manuscript Received: 8 MAY 2005

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Abstract

Due to e-mail's ubiquitous nature, millions of users are intimate with the technology; however, most users are only familiar with managing their own e-mail, which is an inherently different task from exploring an e-mail archive. Historians and social scientists believe that e-mail archives are important artifacts for understanding the individuals and communities they represent. To understand the conversations evidenced in an archive, context is needed. In this article, we present a new way to gain this necessary context: analyzing the temporal rhythms of social relationships. We provide methods for constructing meaningful rhythms from the e-mail headers by identifying relationships and interpreting their attributes. With these visualization techniques, e-mail archive explorers can uncover insights that may have been otherwise hidden in the archive. We apply our methods to an individual's 15-year e-mail archive, which consists of about 45,000 messages and over 4,000 relationships.

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