• Title/Summary/Keyword: Geotagged Tweets

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Comparing the Spatial Mobility of Residents and Tourists by using Geotagged Tweets (지오트윗을 이용한 거주자와 방문자의 공간 이동성 연구)

  • Cho, Jaehee;Seo, Il-Jung
    • Journal of Information Technology Services
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    • v.15 no.3
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    • pp.211-221
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    • 2016
  • The human spatial mobility information is in high demand in various businesses; however, there are only few studies on human mobility because spatio-temporal data is insufficient and difficult to collect. Now with the spread of smartphones and the advent of social networking services, the spatio-temporal data began to occur on a large scale, and the data is available to the public. In this work, we compared the movement behavior of residents and tourists by using geo-tagged tweets which contain location information. We chose Seoul to be the target area for analysis. Various creative concepts and analytical methods are used: grid map concept, cells visited concept, reverse geocoding concept, average activity index, spatial mobility index, and determination of residents and visitors based on the number of days in residence. Conducting a series of analysis, we found significant differences of the movement behavior between local residents and tourists. We also discovered differences in visiting activity according to residential countries and used applications. We expect that findings of this research can provide useful information on tourist development and urban development.

Investigation of Twitter Users' Activity Radius and Home Region in the City: The Case of Las Vegas (트위터 사용자의 도시 내 활동반경과 거주지역의 탐색: 라스베이거스 사례)

  • Cho, Jaehee;Seo, Il-Jung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.2
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    • pp.505-513
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    • 2017
  • In this study, we collected 200,578,703 geo-tweets and removed the twitter bots. Using the concept of activity radius, Twitter users are classified. Users are also divided first into domestic and overseas, and again domestic ones are divided into locals and non-locals. Statistical characteristics of activity strength and active area of Twitter users are described according to activity radius and home region, and the geographical distribution is presented visually. Through a case study of Las Vegas, we have identified the difference in activity strength and active area by the user's home residence. We expect to derive theories about human mobility by analyzing various cities with the method proposed in this study.