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Mapping digital popularity: Analyzing the network attention patterns of national forest parks based on Douyin (Tiktok) data

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  • Shan Zhang
  • Qiuchan Gu

Abstract

The study measures the Network Attention of national forest parks based on user data from the Douyin platform, utilizing the rank-size rule and Jenks natural breaks method to analyze their spatial distribution characteristics, and employing a geographic detector to explore influencing factors. The results indicate a significant imbalance in the Network Attention distribution of national forest parks, characterized by a steep downward trend. The top parks have high attention but are few in number, while the bottom parks are numerous but receive less attention. Further investigation reveals that the spatial differentiation of Network Attention results from the synergistic drive of multiple factors. Regional economic development and the level of internet penetration emerge as critical single drivers, while factor interactions universally exhibit enhancement effects. This study provides empirical support for formulating differentiated digital dissemination strategies for national forest parks, enhancing social influence, and fostering public participation, holding significant implications for promoting ecological protection and the sustainable development of eco-tourism.

Suggested Citation

  • Shan Zhang & Qiuchan Gu, 2026. "Mapping digital popularity: Analyzing the network attention patterns of national forest parks based on Douyin (Tiktok) data," PLOS ONE, Public Library of Science, vol. 21(3), pages 1-16, March.
  • Handle: RePEc:plo:pone00:0344983
    DOI: 10.1371/journal.pone.0344983
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    1. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
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