基于UGC数据的徐州市旅游流网络空间结构研究

唐雯, 王德鲁, 杨礼娟

高科技与产业化 ›› 2025, Vol. 31 ›› Issue (9) : 67.

主管:中国科学院
主办:中国科学院文献情报中心、中国高科技产业化研究会
ISSN:1006-222X
CN:11-3556/N
高科技与产业化 ›› 2025, Vol. 31 ›› Issue (9) : 67.

基于UGC数据的徐州市旅游流网络空间结构研究

  • 唐雯雯1,2,王德鲁1,杨礼娟3
作者信息 +

Research on the Spatial Structure of Tourism Flow Network in Xuzhou City Based on UGC Data

  • TANG Wenwen1,2,WANG Delu1,YANG Lijuan3
Author information +
文章历史 +

摘要

自助旅游流网络结构研究,是旅游研究的重要内容。本研究基于徐州市的旅游UGC数据,构建旅游节点旅游流网络,运用社会网络分析法,从描述性特征、中心度、结构洞等方面探讨徐州市自助旅游流网络结构特征。主要结论如下:(1)徐州市节点类型丰富,旅游线路出游时间以1—3天短程旅游为主,平均节点数为4.21;(2)徐州博物馆、宝莲寺、云龙湖、龟山汉墓及云龙山为门户目的地节点;(3)整体网络密度低,不同节点在徐州市旅游网络中的地位不同,云龙湖、回龙窝、户部山、宝莲寺、徐州博物馆及云龙山结构洞优势明显。

Abstract

The study of the network structure of self-service tourism flow is an important aspect of tourism research. Based on the tourism UGC data of Xuzhou City, a tourism node tourism flow network is constructed, and social network analysis is used to explore the structural characteristics of Xuzhou City’s self-service tourism flow network from the aspects of descriptive features, centrality, structural holes. The main conclusions are as follows: (1) Xuzhou City has a rich variety of node types, with tourism routes mainly taking 1-3 days for short distance travel, with an average node number of 4.21; (2) Xuzhou Museum, Baolian Temple, Yunlong Lake, Guishan Han Tomb, Yunlong Mountain Portal Destination Node; (3) The overall network density is low, and different nodes have different positions in the tourism network of Xuzhou City. Yunlong Lake, Huilongwo, Hubu Mountain, Baolian Temple, Xuzhou Museum, and Yunlong Mountain have obvious advantages in structural caves.

关键词

旅游流 / 社会网络 / UGC数据 / 徐州

Key words

tourism flow / social networks / UGC, Xuzhou

引用本文

导出引用
唐雯, 王德鲁, 杨礼娟. 基于UGC数据的徐州市旅游流网络空间结构研究[J]. 高科技与产业化. 2025, 31(9): 67
TANG Wenwen, WANG Delu1, YANG Lijuan. Research on the Spatial Structure of Tourism Flow Network in Xuzhou City Based on UGC Data[J]. High-Technology and Commercialization. 2025, 31(9): 67

Accesses

Citation

Detail

段落导航
相关文章

/