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Knowledge, Information and Creativity Support Systems pp 521–528Cite as

A Method for Opinion Mining of Coffee Service Quality and Customer Value by Mining Twitter

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 416))

Abstract

In this work, we focus on customer value of Japanese coffee service by analyzing the huge tweet data set. We suggest the quantitative evaluation method of customer value by using the morphological analysis of the tweets and generated value dictionary. Our suggested methodology can be applied to any service and product to improve the commoditization problem from the viewpoint of service science.

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Notes

  1. 1.

    International Coffee Organization—Historical data.

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Author information

Authors and Affiliations

  1. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Shu Takahashi & Youji Kohda

  2. Faculty of Humanities, Yamanashi Eiwa College, Yamanashi, Japan

    Ayumu Sugiyama

Authors
  1. Shu Takahashi
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  2. Ayumu Sugiyama
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  3. Youji Kohda
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Corresponding author

Correspondence to Ayumu Sugiyama .

Editor information

Editors and Affiliations

  1. and Technology, JAIST - Japan Advanced Institute for Sci, Kanazawa, Japan

    Susumu Kunifuji

  2. Dept of Computer Science, University of Cyprus, Nicosia, Cyprus

    George Angelos Papadopoulos

  3. Dept. of Automatic Control & Biom. Eng., AGH University of Science and Technology, Kraków, Poland

    Andrzej M.J. Skulimowski

  4. Systems Res Inst, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk  

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© 2016 Springer International Publishing Switzerland

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Takahashi, S., Sugiyama, A., Kohda, Y. (2016). A Method for Opinion Mining of Coffee Service Quality and Customer Value by Mining Twitter. In: Kunifuji, S., Papadopoulos, G., Skulimowski, A., Kacprzyk  , J. (eds) Knowledge, Information and Creativity Support Systems. Advances in Intelligent Systems and Computing, vol 416. Springer, Cham. https://doi.org/10.1007/978-3-319-27478-2_39

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  • DOI: https://doi.org/10.1007/978-3-319-27478-2_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27477-5

  • Online ISBN: 978-3-319-27478-2

  • eBook Packages: EngineeringEngineering (R0)

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