Changes in Street Fashion Networks Using Social Big Data : Time-Series Approach to Public Attention and Cluster Attributes

Seon, Joon-Ho; Jung, Hye-Jung; Lee, Ji-Yeon

doi:10.7233/jksc.2021.71.3.124

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…In performing QAP correlation analysis, the nodes and matrix sizes that comprise these independent and dependent matrices must match each other [38]. Therefore, we applied a matrix of 100 keywords for each time period.…”

Section: Qap Correlation Analysis Resultsmentioning

confidence: 99%

Changes in Social Media Big Data on Healing Forests: A Time-Series Analysis on the Use Behavior of Healing Forests before and after the COVID-19 Pandemic in South Korea

Youn,

Kim

2024

Forests

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This study aimed to identify changes in visitor behavior and visitor interest in healing forests before and after the COVID-19 pandemic. The study used text mining analysis techniques to identify changes in visitation behavior over time, divided into three periods, as follows: pre-COVID-19 (1 January to 31 December 2019), during the COVID-19 pandemic (1 November 2020 to 31 October 2022), and post-COVID-19 (1 November 2022 to 31 October 2023). After the COVID-19 outbreak, healing forest use behavior did not revert to pre-COVID-19 patterns. Moreover, the keywords “tourism” and “hiking” stood out as the main drivers of this change in behavior. Therefore, the Korea Forest Service and related authorities must examine the scalability of the functions, services, and programs of healing forests from a general healing space to a space for leisure and tourism. These findings will contribute to the development of future marketing strategies and programs for healing forests.

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Section: Qap Correlation Analysis Resultsmentioning

confidence: 99%

Changes in Social Media Big Data on Healing Forests: A Time-Series Analysis on the Use Behavior of Healing Forests before and after the COVID-19 Pandemic in South Korea

Youn,

Kim

2024

Forests

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Changes in Social Media Big Data on Healing Forests : A Time-series Analysis on the Use Behavior of Healing Forests Before and After the COVID-19 Pandemic in South Korea

Kim,

Youn

2024

Preprint

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This study aimed to identify changes in visitor behavior and visitor interest in healing forests before and after the COVID-19 pandemic. The study used text mining analysis techniques to identify changes in visitation behavior over time, divided into three periods: pre-COVID-19 (January 1 to December 31, 2019), during the COVID-19 pandemic (November 1, 2020 to October 31, 2022), and post-COVID-19 (November 1, 2022 to October 31, 2023 ). After the COVID-19 outbreak, healing forest use behavior did not regress to pre-COVID-19 levels. Activity-based keywords such as "hiking," "trekking," and "walking" stood out as the main drivers of this change in behavior. Therefore, related authorities must examine the scalability of the functions, services, and programs of healing forests from a general healing space to a space for leisure and tourism. These findings will contribute to the development of future marketing strategies and programs for healing forests.

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A Study on Fashion Design Characteristics of Indonesian Muslim Women through Street Fashion : Focused on Bandung City, West Java

Yang¹,

Setiawardhani²,

Park³

2021

jksc

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Changes in Street Fashion Networks Using Social Big Data : Time-Series Approach to Public Attention and Cluster Attributes

Cited by 3 publications

References 15 publications

Changes in Social Media Big Data on Healing Forests: A Time-Series Analysis on the Use Behavior of Healing Forests before and after the COVID-19 Pandemic in South Korea

Changes in Social Media Big Data on Healing Forests: A Time-Series Analysis on the Use Behavior of Healing Forests before and after the COVID-19 Pandemic in South Korea

Changes in Social Media Big Data on Healing Forests : A Time-series Analysis on the Use Behavior of Healing Forests Before and After the COVID-19 Pandemic in South Korea

A Study on Fashion Design Characteristics of Indonesian Muslim Women through Street Fashion : Focused on Bandung City, West Java

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