Estimating Temporal Dynamics of Human Emotions

Authors

  • Seungyeon Kim Georgia Institute of Technology
  • Joonseok Lee Georgia Institute of Technology
  • Guy Lebanon Amazon
  • Haesun Park Georgia Institute of Technology

DOI:

https://doi.org/10.1609/aaai.v29i1.9190

Abstract

Sentiment analysis predicts a one-dimensional quantity describing the positive or negative emotion of an author. Mood analysis extends the one-dimensional sentiment response to a multi-dimensional quantity, describing a diverse set of human emotions. In this paper, we extend sentiment and mood analysis temporally and model emotions as a function of time based on temporal streams of blog posts authored by a specific author. The model is useful for constructing predictive models and discovering scientific models of human emotions.

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Published

2015-02-09

How to Cite

Kim, S., Lee, J., Lebanon, G., & Park, H. (2015). Estimating Temporal Dynamics of Human Emotions. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9190