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http://dx.doi.org/10.9715/KILA.2020.48.1.035

A Time Series Analysis of Urban Park Behavior Using Big Data  

Woo, Kyung-Sook (Graduate School of Landscape Architecture, Kyung Hee University)
Suh, Joo-Hwan (Dept. of Landscape Architecture, Kyung Hee University)
Publication Information
Journal of the Korean Institute of Landscape Architecture / v.48, no.1, 2020 , pp. 35-45 More about this Journal
Abstract
This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.
Keywords
Big Data; Usage Characteristics; Behavior Analysis; Text Mining; Social Networks;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Astri, W. and Y. M. Kim(2015) Correlation between social activities and the physical characteristics of urban parks: -Urban parks in bandung. Indonesia Urban Design Institute of Korea 16(2): 17-32.
2 Borgatti, S. P., A. Mehra, D. J. Brass, and G. Labianca(2009) Net work analysis in the social sciences. Science 323(5916): 892-895.   DOI
3 Choi, H. K(2009) The Instrumental Proposal That is Based on The Human Behavior and Space Trait. Master's Thesis. Sungkyunkwan University.
4 Freeman, L. C.(1979) Centrality in social networks conceptual clarific ation. Social Networks, 1:215-239.   DOI
5 Friedkin, N.(1993) Structural bases of interpersonal influence in groups: A longitudinal case study. American Sociological Review 58: 861-872.   DOI
6 Gwak, K. Y.(2017) Social Network Analysis, Chungram.
7 Lee, E. J.(2008) The Public Resting Place Design Plan Considering User Behavior in Downtown Area. Master's Thesis. Kookmin University.
8 Im, S. B.(1998) Environmental Psychology, Bosung.
9 Jacobs, J.(2010) Death and Life of Great American Cities, Greenbee.
10 Kim, S. B.(2015) Blog text analysis about visitors' experience change of Seochon. The Architectural Institute of Korea 31(6): 93-102.   DOI
11 Lee, J. H.(2013) Big data and social sciences: epistemological and methodological issues. Korean Society for Journalism & Communication Studies 9(3): 127-165.
12 Lee, J. S.(2012) Study on The Spatial Network Structure and Characteristics of Leisure Movement for Seoul Metropolitan Area. Ph.D. Dissertation. Kyungki University.
13 Lee, K. W.(2007) Korean Quality of life Development Basic Research, Korea Culture & Tourism Institute.
14 Leem, B. H.(2012) An effect of co-authorship network on research performance: Focusing on co-authoring of logos management review. Korean Association of rkwhr7292-Logos Management 10(1): 1-20.
15 Woo, K. S. and J. H. Suh(2018) Time series analysis of park use behavior utilizing big data - Targeting Olympic park -. Journal of the Korean Institute of Landscape Architecture 46(2): 27-36.   DOI
16 Yun, Y. S. and E. S. Kim(2004) Leisure Activity Changes and Outdoor Recreation Resources Development in the Capital Region, KRIHS.