| Abstract |
| This research aimed to recognize the determinant characteristics affecting consumers' clothing fit evaluation by employing text mining and social network analysis. For this aim, we first extracted text data linked to clothing fit from 2,000 consumer reviews collected from social network services and conducted semantic network examination and CONCOR analysis. As a result, we reported that “pants” and “skirts” were the most commonly associated clothing items with consumers' clothing fit evaluation. And the length of clothing was most commonly investigated. Then, the “waist” and “hip” were the most critical body parts affecting consumers' perception of clothing fit. Further, the four keywords including “wide,” “large,” “short,” and “long” were the most employed ones in consumer reviews when evaluating clothing fit. This study is meaningful in that it specifically recognized the structural relationship and semantic meanings of keywords relevant to consumers' evaluation of clothing fit, which could bring empirical reference information for advanced clothing fit. |
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| Key Words |
| Clothing, Fit, Evaluation, Text Data, Social Network Analysis, 의복, 맞음새, 평가, 텍스트 데이터, 소셜 네트워크 분석 |
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