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On-Site Likelihood Identification of Tweets Using a Two-Stage Method

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Tourism Informatics

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 90))

Abstract

The Web contains much information for the tourism, such as impressions and sentiments about sightseeing areas. Analyzing the information is a significant task for tourism informatics. A useful target resource for the analysis is information on Twitter. However, all tweets with keywords, which are related to facilities and events for tourism, might not be tourism information. In this paper, we propose a method for estimating on-site likelihood of tweets. The task is to identify whether each tweet has high on-site likelihood or not. We introduce a filtering process and a machine learning technique for the task. In addition, we apply previous and next tweets for the identification task, as context information. Experimental results show the effectiveness of the combination method and context information.

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Notes

  1. 1.

    http://4travel.jp/.

  2. 2.

    http://travel.blogmura.com/.

  3. 3.

    http://twitter.com.

  4. 4.

    It is a famous temple in Kyoto.

  5. 5.

    E.g., the 1st and 3rd tweets of User D in Fig. 6.3.

  6. 6.

    It is \(721+(3114-1337)\) in Table 6.1.

  7. 7.

    In this case, the proposed method sacrificed the recall rate of 4.4 % in the filtering process.

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Authors and Affiliations

  1. Kyushu Institute of Technology, 680-4, Iizuka, Fukuoka, Japan

    Kazutaka Shimada, Yurie Onitsuka, Shunsuke Inoue & Tsutomu Endo

Authors
  1. Kazutaka Shimada
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  2. Yurie Onitsuka
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  3. Shunsuke Inoue
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  4. Tsutomu Endo
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Corresponding author

Correspondence to Kazutaka Shimada .

Editor information

Editors and Affiliations

  1. Graduate School of Industrial Technology, Advanced Institute of Industrial Technology, Shinagawa, Tokyo, Japan

    Tokuro Matsuo

  2. School Sustainable System Sciences, Osaka Prefecture University, Osaka, Japan

    Kiyota Hashimoto

  3. Department of Wellness Tourism, Josai International University, Chiba, Japan

    Hidekazu Iwamoto

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Shimada, K., Onitsuka, Y., Inoue, S., Endo, T. (2015). On-Site Likelihood Identification of Tweets Using a Two-Stage Method. In: Matsuo, T., Hashimoto, K., Iwamoto, H. (eds) Tourism Informatics. Intelligent Systems Reference Library, vol 90. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47227-9_6

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  • DOI: https://doi.org/10.1007/978-3-662-47227-9_6

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  • Print ISBN: 978-3-662-47226-2

  • Online ISBN: 978-3-662-47227-9

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