Analysis of outdoor-wear research trends using topic modeling 토픽 모델링을 이용한 아웃도어웨어 연구 동향 분석
pp.53-69
This study aims to analyze research trends regarding outdoor wear. For this purpose, the data-collection period was limited to January 2002–October 2022, and the collection consisted of titles of papers, academic names, abstracts, and publication years from the Research Information Sharing Service (RISS). Frequency analysis was conducted on 227 papers in total to check academic journals and annual trends, and LDA topic-modeling analysis was conducted using 20,964 tokens. Data pre-processing was performed prior to topic-modeling analysis; after that, topic-modeling analysis, core topic derivation, and visualization were performed using a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: experiential marketing and lifestyle, property and evaluation of outdoor wear, design and patterns of outdoor wear, outdoor-wear purchase behavior, color, designs and materials of outdoor wear, promotional strategies for outdoor wear, purchase intention and satisfaction depending on the brand image of outdoor wear, differences in outdoor wear preferences by consumer group. The results of topic-modeling analysis revealed that the topic, which includes a study on the design and material of outdoor wear and the pattern of jackets related to the overall shape, was the highest at 30.9% of the total topics. The next highest topic was also the design and color of outdoor wear, indicating that design-related research was the main research topic in outdoor wear research. It is hoped that analyzing outdoor wear research will help comprehend the research conducted thus far and reveal future directions.
I. Introduction
Ⅱ. Literature Review
1.Analysis of research trend in the apparel study
2. LDA topic modeling
Ⅲ. Methods
1. Data collection
2. Data analysis
Ⅳ. Results
1. Distribution status of outdoor wear-related papers by year and by academic journal
2. Topic modeling analysis results
Ⅴ. Conclusion
References