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Searching Comprehensive Web Pages of Multiple Sentiments for a Topic

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Transactions on Engineering Technologies

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Abstract

We have developed a novel system for searching comprehensive Web pages by focusing on multiplicity of sentiments of writers for a topic. Recently, lots of studies and services based on sentiment analysis have been conducted, since it is still difficult to search and summarize information satisfying users’ needs by text analysis only. In this paper, we propose a system for searching and visualizing comprehensive Web pages in terms of sentiments by extracting multiple sentiments of Web pages on a query topic and re-retrieving Web pages using sub-topic keywords. Specifically, this system extracts sentiment features of each Web page using a sentiment dictionary consisting of three sentiment dimensions; “Happy ⇔ Sad,” “Glad ⇔ Angry,” and “Peaceful ⇔ Strained.” Next, in order to conduct a re-retrieval, it extracts sub-topic keywords from Web pages of maximum (or minimum) sentiment features on three sentiment dimensions, respectively. Then, it re-retrieves Web pages using the query topic keyword and the extracted sub-topic keywords. Then, it plots them on sentiment graphs based on their sentiment features. By using the graphs, we can grasp not only sentiment tendency but also comprehensive sentiments for a query topic. In the experiment, we evaluate our proposed method using the developed system.

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Notes

  1. 1.

    Google Web Search API: https://developers.google.com/web-search/docs/.

  2. 2.

    Since the title and snippet of a Web page summarize the content of the page and their text is shorter than the full page, the system actually calculates the sentiment features using the text of the title and snippet for each page so as to shorten the response time.

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Acknowledgments

This research was supported in part by Strategic Information and Communications R&D Promotion Programme (SCOPE), the Ministry of Internal Affairs and Communications of Japan, and JSPS KAKENHI Grant Numbers 24780248, 26280042, 26330347, 26330351, and 26870090.

Author information

Authors and Affiliations

  1. Kyoto Sangyo University, Kyoto, Japan

    Shoko Wakamiya & Yukiko Kawai

  2. Chiba Institute of Technology, Narashino, Japan

    Tadahiko Kumamoto

  3. Tsukuba University of Technology, Tsukuba, Japan

    Jianwei Zhang & Yuhki Shiraishi

Authors
  1. Shoko Wakamiya
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  2. Yukiko Kawai
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  3. Tadahiko Kumamoto
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  4. Jianwei Zhang
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  5. Yuhki Shiraishi
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Corresponding author

Correspondence to Shoko Wakamiya .

Editor information

Editors and Affiliations

  1. Multimedia Engineering College of Engioneering, Mokpo National University, Chonnam, Korea, Republic of (South Korea)

    Gi-Chul Yang

  2. Unit 1, 1/F, Hung To Road, IAENG Secretariat, International Association of Engine, Hong Kong, Hong Kong SAR

    Sio-Iong Ao

  3. Faculty of Information Sciences and Engineering, University of Canberra, Canberra, Aust Capital Terr, Australia

    Xu Huang

  4. Calzada Tecnologico s/n, Instituto Tecnologico de Tijuana, Tijuana, Baja California, Mexico

    Oscar Castillo

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Wakamiya, S., Kawai, Y., Kumamoto, T., Zhang, J., Shiraishi, Y. (2015). Searching Comprehensive Web Pages of Multiple Sentiments for a Topic. In: Yang, GC., Ao, SI., Huang, X., Castillo, O. (eds) Transactions on Engineering Technologies. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9588-3_26

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  • DOI: https://doi.org/10.1007/978-94-017-9588-3_26

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-017-9587-6

  • Online ISBN: 978-94-017-9588-3

  • eBook Packages: EngineeringEngineering (R0)

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