텍스트마이닝을 통한 10년간 소비자 세탁행동 요구의 변화
A Decade of Shifting Consumer Laundry Needs Through Text Mining Analysis
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In recent years, consumer clothing behaviors have undergone significant changes due to global phenomena such as climate change, pandemics, and advances in IT technology. Laundry behaviors closely connected to how consumers handle clothes and their clothing lifecycle have also experienced considerable transformations. However, research on laundry behavior has been limited despite its importance in understanding consumer clothing habits. This study employed text mining analysis of social data spanning the past decade to explore overall trends in consumer laundry behavior, aiming to understand key topics of interest and changes over time. Through LDA topic modeling analysis, nine topics were identified. They were grouped into subjects, targets, methods, and reasons related to laundry. Analyzing relative frequencies of keywords for each topic group revealed evolving consumer laundry behavior in response to societal changes. Over time, laundry behavior showed a dispersal of agents and locations, increased diversification of laundry targets, and a growing interest in various methods and reasons for doing laundry. This research sheds light on the broader context of laundry behavior, offering a more comprehensive understanding of consumer attitudes and perceptions than previous studies. It underscores the significance of laundry as a daily, socio-cultural aspect of our lives. Additionally, this study identifies changing customer values and suggests improvements and strategic branding for laundry services, providing practical implications.
Abstract
In recent years, consumer clothing behaviors have undergone significant changes due to global phenomena such as climate change, pandemics, and advances in IT technology. Laundry behaviors closely connected to how consumers handle clothes and their clothing lifecycle have also experienced considerable transformations. However, research on laundry behavior has been limited despite its importance in understanding consumer clothing habits. This study employed text mining analysis of social data spanning the past decade to explore overall trends in consumer laundry behavior, aiming to understand key topics of interest and changes over time. Through LDA topic modeling analysis, nine topics were identified. They were grouped into subjects, targets, methods, and reasons related to laundry. Analyzing relative frequencies of keywords for each topic group revealed evolving consumer laundry behavior in response to societal changes. Over time, laundry behavior showed a dispersal of agents and locations, increased diversification of laundry targets, and a growing interest in various methods and reasons for doing laundry. This research sheds light on the broader context of laundry behavior, offering a more comprehensive understanding of consumer attitudes and perceptions than previous studies. It underscores the significance of laundry as a daily, socio-cultural aspect of our lives. Additionally, this study identifies changing customer values and suggests improvements and strategic branding for laundry services, providing practical implications.
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