Using Social Media Text Data to Analyze the Characteristics and Influencing Factors of Daily Urban Green Space Usage—A Case Study of Xiamen, China

Author:

Fan Chenjing12,Li Shiqi1,Liu Yuxin1,Jin Chenxi1,Zhou Lingling1,Gu Yueying1,Gai Zhenyu1ORCID,Liu Runhan1,Qiu Bing1

Affiliation:

1. College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China

2. Jinpu Research Institute, Nanjing Forestry University, Nanjing 210037, China

Abstract

While urban green spaces (UGSs) are important places for residents’ leisure activities, studies describing the long-term daily UGS usage of residents (including the total number of activities, the types of activities, and the touring experience) have not been conducted due to difficulties in data collection. Based on social media text data (SMTD), in this study, the total number of daily activities, the intensities of optional and social activities, and the daily touring experience in 100 UGSs in Xiamen, China, were inferred based on the ERNIE 3.0 text pre-training semantic classification model. Based on this, linear regression modeling was applied to analyze the internal environmental factors of the effects of places and external urban form factors regarding daily UGS usage. The research results revealed the following. (1) A descriptive study was conducted on the total numbers, types, and touring experience of activities using SMTD, and the results were verified by line transect surveys, management statistics, and a publicly available dataset. (2) The number of human activities in UGSs was found to be significantly influenced by historical and cultural facilities, nighttime lighting, population density, and the proportion of the floating population. (3) During the daytime, optional activities were found to be significantly influenced by the park type and historical and cultural facilities, and social activities were found to be significantly influenced by historical and cultural facilities and population density. In the evening, optional activities were found to be significantly influenced by the park type, historical and cultural facilities, nighttime lighting, and the proportion of the floating population, and social activities were found to be influenced by the proportion of the floating population. (4) Regarding the touring experience, in the daytime, the park type, green space ratio, and proportion of the floating population had significant effects on the touring experience. In the evening, the park type, historical and cultural facilities, and security factors were found to have significant effects on the touring experience. The methodology and findings of this study aid in the understanding of the differences in daytime and nighttime activities, and in the discovery of planning tools to promote human leisure activities in UGSs.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Forestry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3