Extraction and analysis of city's tourism districts based on social media data

Hu Shao, Yi Zhang, WenWen Li

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Through the perspective of tourism, a city as a tourist destination usually consists of multiple tourist attractions such as natural or cultural scenic spots. These attractions scatter in city spaces following some specific forms: clustered in some regions and dispersed in others. It is known that users organize their tours in a city not only according to the distance between different attractions but also according to other factors such as time constraints, expenses, interests, and the similarities between different attractions. Hence, users' travel tours can help us gain a better understanding about the relationships among different attractions at the city scale. In this paper, a methodological framework is developed to detect tourists' spatial-temporal behaviors from social media data, and then such information is used to extract and analyze city's tourism districts. We believe that this city space division will make significant contributions to the fields of urban planning, tourism facility providing, and scenery area constructing. A typical tourism city in China—Huangshan—is selected as our study area for experiments.

Original languageEnglish (US)
Pages (from-to)66-78
Number of pages13
JournalComputers, Environment and Urban Systems
Volume65
DOIs
StatePublished - Sep 2017

Keywords

  • Social media
  • Spatial-temporal behavior
  • Tourism district

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Ecological Modeling
  • Environmental Science(all)
  • Urban Studies

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