CollectHomepage AdvertisementContact usMessage

Arid Land Geography ›› 2026, Vol. 49 ›› Issue (6): 1264-1276.doi: 10.12118/j.issn.1000-6060.2025.582

• Tourism Geography • Previous Articles     Next Articles

Spatial characteristics and influencing factors of “internet celebrity spots punch in” based on social media data

ZHU Yiting1(), DU Yue1, ZHOU Yuqian2, HE Xiong3, ZHOU Chunshan3(), CHEN Hongrui1   

  1. 1 School of Tourism, Xinjiang University, Key Laboratory of Sustainable Development of Xinjiang’s Historical and Cultural Touism, Urumqi 830046, Xinjiang, China
    2 School of Media Studies, Xinjiang Arts University, Urumqi 830023, Xinjiang, China
    3 School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, Guangdong, China
  • Received:2025-09-23 Revised:2025-10-09 Online:2026-06-25 Published:2026-06-29
  • Contact: ZHOU Chunshan E-mail:yiting@xju.edu.cn;zhoucs@mail.sysu.edu.cn

Abstract:

Using Xiaohongshu “check-in” posts, “internet celebrity spots puch in” in Urumqi City are classified into seven categories: Commercial shopping, dining and cuisine, tourism landmarks, leisure and entertainment, specialty retail, cultural venues, and historical architecture. Employing spatial analysis methods in ArcGIS, including average nearest neighbor, kernel density estimation and hotspot analysis, this study examines their spatial distribution. The geographic detector is further applied to identify influencing factors. The results show the following: (1) These spots exhibit an agglomerated spatial structure, generally “dense in the south and sparse in the north, dense in the interior and sparse in the periphery”, characterized by “single core and multiple points”. (2) Hotspot areas are consistent with the urban development patterns, specifically six areas, namely Zhongshan Road, Hongshan Road, Youhao Road, Railway Bureau, Hongguang Mountain, and Kashi Road. (3) The spatial distribution is strongly influenced by economic scale, consumer demand and transportation layout, with significant variation in how these indicators drive spatial heterogeneity.

Key words: “internet celebrity spots punch in”, social media, spatial distribution, Geodetector, Xiaohongshu