| Title |
Analyzing Visitor Behavior in Complex Shopping Mall Through Text Mining |
| DOI |
https://doi.org/10.5659/JAIK.2024.40.12.37 |
| Keywords |
Timesquare; The Hyundai Seoul; Behavior; Text Mining; Social Networking Service(SNS) |
| Abstract |
This study analyzes visitor behavior at Timesquare and The Hyundai Seoul shopping malls to understand usage patterns and present
improvement strategies. Blog data from Naver and Daum, covering Feb. 2021 to Feb. 2022 (P1) and Feb. 2023 to Feb. 2024 (P2), was used
for text-mining and analysis. The findings are as follows: visitor behaviors were classified as dynamic such as eat, buy, explore and take
photos, and static such as sit, see, wait and line up. The buy behavior was not among the top keywords, likely reflecting the trends of the
MZ generation browsing in-store but making purchases online. During the P1 period of COVID-19, must-eat places were key attractions at
both malls. In the P2 period, after COVID-19, pop-up stores also became sinificant draws. While spacious environments enhance appeal and
visitor stay time, entertainment elements like specialized dining and pop-up events are crucial for encouraging repeat visits and generating
new interest. |