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Discussion Analysis Using Temporal Data Crystallization

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New Frontiers in Artificial Intelligence (JSAI-isAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7856))

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Abstract

This paper introduces a discussion analysis tool which extracts topic flow and important utterances from a discussion record based on word occurrences. We have proposed a discussion analysis method called Temporal Data Crystallization (TDC). This method divides the entire discussion record hierarchically at points where the topic changes, and analyzes some features of flow of topics for each period. In this paper, we showed the effect of hierarchical division by analyzing an example discussion record. Then, we introduced the extension of TDC by considering nonverbal information such as actions, facial expression, loudness of voice, and so on.

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Author information

Authors and Affiliations

  1. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan

    Masaki Sugimoto, Takahiro Ueda, Shogo Okada & Katsumi Nitta

  2. Department of Systems Innovation, The University of Tokyo, Tokyo, Japan

    Yukio Ohsawa

  3. Social Design Group, Tokyo, Japan

    Yoshiharu Maeno

Authors
  1. Masaki Sugimoto
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  2. Takahiro Ueda
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  3. Shogo Okada
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  4. Yukio Ohsawa
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  5. Yoshiharu Maeno
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  6. Katsumi Nitta
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Editor information

Editors and Affiliations

  1. National Institute of Advanced Industrial Science and Technology (AIST), Japan

    Yoichi Motomura

  2. Tohoku University, Kawauchi 41, 980-8576, Aoba-ku, Sendai, Japan

    Alastair Butler

  3. Ochanomizu University, 2-1-1 Bunkyo-ku, 122-8610, Tokyo, Japan

    Daisuke Bekki

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© 2013 Springer-Verlag Berlin Heidelberg

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Sugimoto, M., Ueda, T., Okada, S., Ohsawa, Y., Maeno, Y., Nitta, K. (2013). Discussion Analysis Using Temporal Data Crystallization. In: Motomura, Y., Butler, A., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2012. Lecture Notes in Computer Science(), vol 7856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39931-2_15

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  • DOI: https://doi.org/10.1007/978-3-642-39931-2_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39930-5

  • Online ISBN: 978-3-642-39931-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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