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Stability of a Type of Cross-Cultural Emotion Modeling in Social Media

  • Monte HancockEmail author
  • Chad Sessions
  • Chloe Lo
  • Shakeel Rajwani
  • Elijah Kresses
  • Cheryl Bleasdale
  • Dan Strohschein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9183)

Abstract

Humankind has thousands of years of experience in assessing the emotional context of face-to-face interaction. Written communication has been refined over centuries, and imme-diate voice communication over decades. However, online communication, which tends to be asynchronous and largely empty of conventional social cues, is still emerging as a cultural and cognitive venue. In this paper we present the earliest results of applying our field-theory of “emotional context” to the problem of the cross-cultural online emotion modeling:

Can a field-theoretic model developed using data from one culture be applied to online interaction in another?

We also present the results of a small empirical study focusing on the methods we used to visualize and model the “emotional context” of a social media corpus.

Keywords

Social Medium Emotional Context Emotion Modeling Text Feature Extraction Output Text 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Lee, S., Song, J., Kim, Y.: An empirical comparison of four text mining methods (2010)Google Scholar
  2. 2.
    Torgerson, W.S.: Theory & Methods of Scaling. Wiley, New York (1958). ISBN 0-89874-722-8Google Scholar
  3. 3.
    Hancock, M.: Practical Data Mining. CRC Press, Boca Raton (2011). ISBN 13: 978-1439868362Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Monte Hancock
    • 1
    Email author
  • Chad Sessions
    • 2
  • Chloe Lo
    • 2
  • Shakeel Rajwani
    • 2
  • Elijah Kresses
    • 2
  • Cheryl Bleasdale
    • 2
  • Dan Strohschein
    • 3
  1. 1.4DigitalLondonUK
  2. 2.Sirius15Washington, DCUSA
  3. 3.National Aeronautics and Space AdministrationWashington, DCUSA

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