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Measuring Serial Emotional Content in the Enron Email Corpus

Burk, Scott William, 1961-, author. ;Bilisoly, Roger, 1963-, thesis advisor.


Available at Central Connecticut State University  CCSU Theses/Dissertations Stack 6  (Thesis 2264 )()

  • Title:
    Measuring Serial Emotional Content in the Enron Email Corpus
  • Author/Creator: Burk, Scott William, 1961-, author.
  • Bilisoly, Roger, 1963-, thesis advisor.; Central Connecticut State University. Department of Mathematical Sciences.
  • Creation Date: 2012
  • Language: English
  • Physical Description: 103 leaves : color illustrations ; 29 cm.
  • Bibliography: Includes bibliographical references (leaves 69-77)
  • Subjects: Enron Corp -- Databases; Electronic mail messages -- Databases; Data mining
  • Description: The Enron corpus is one of the few publically available corporate email datasets. It contains over a half million email messages, which has been used in a variety of academic disciplines for research. The purpose of this thesis is to explore methods to measure emotional content across emails contained within the Enron email corpus longitudinally. In this context we define a longitudinal study as an analysis of a measure or measures of interest over time, which is important because it allows us to compare the relative change in emotional content across this dimension. The events that define the history of Enron are well documented, and we analyze its emails to find correlations over time between the events and emotional content in the emails. We believe similar studies can be conducted in other companies to successfully mine corporate data, track employee emotion and use this information to take corrective action. Obviously, Enron had foundational, ethical and legal problems, yet the model serves an exceptional case and its example may be useful for less extreme circumstances. For instance, this project would allow a company to measure the attitudes of employees toward their healthcare coverage via the email information on corporate servers.
  • Notes: Includes bibliographical references (leaves 69-77)
  • Degree Granted: M.S. Central Connecticut State University, 2012.
  • OCLC Number: 819339008