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Tourism Image Perception of Country Parks in Shanghai Based on Web Text Analysis: A Case Study in Pujiang Country Park

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Advances in Human Factors in Architecture, Sustainable Urban Planning and Infrastructure (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 272))

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Abstract

This paper studies the tourism image perception of Pujiang Country Park in Shanghai based on web text analysis. The software Rost Content Mining is used to carry out high-frequency word analysis, semantic network analysis and sentiment analysis on the visitors’ online comment text. The conclusion shows that the visitors’ tourism image perception includes four aspects: featured scenic spot, environment, activity experience, facilities and service. It also shows that the visitors generally have a positive perception, but the causes of negative attitudes can’t be ignored. Finally, suggestions are put forward for the optimal design and management of country parks in Shanghai.

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Authors and Affiliations

  1. School of Art Design And Media, East China University of Science and Technology, Shanghai, 200237, China

    Weiqian Zhang & Tianhong Fang

Authors
  1. Weiqian Zhang
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  2. Tianhong Fang
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Corresponding author

Correspondence to Tianhong Fang .

Editor information

Editors and Affiliations

  1. Department of Architecture, Wroclaw University of Technology, Wroclaw, Poland

    Jerzy Charytonowicz

  2. Institute of Architecture and Urban Planning ul, University of Zielona Gora, Zielona Góra, Poland

    Alicja Maciejko

  3. Doctorate Researcher in Design, Recife-PE, Brazil

    Christianne S. Falcão

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Zhang, W., Fang, T. (2021). Tourism Image Perception of Country Parks in Shanghai Based on Web Text Analysis: A Case Study in Pujiang Country Park. In: Charytonowicz, J., Maciejko, A., Falcão, C.S. (eds) Advances in Human Factors in Architecture, Sustainable Urban Planning and Infrastructure. AHFE 2021. Lecture Notes in Networks and Systems, vol 272. Springer, Cham. https://doi.org/10.1007/978-3-030-80710-8_32

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  • DOI: https://doi.org/10.1007/978-3-030-80710-8_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80709-2

  • Online ISBN: 978-3-030-80710-8

  • eBook Packages: EngineeringEngineering (R0)

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