This study conducted text mining on fashion prompts and derived their components to develop a systematic approach to fashion prompt engineering, with the aim of producing results that clearly reflect the designer's intent through human-AI interaction in generating fashion images. As a research method, text mining was performed on 947 fashion prompts shared in a text-to-image AI online database, with the components of the fashion prompts appropriately organized. The results of this study are summarized as follows: First, word frequency and TF-IDF analysis showed that words related to high-fashion photos capturing full-body shots of fashion models or women; highly detailed images on the theme of complex fashion and realistic depictions; image quality; and MidJourney parameters were frequently used in fashion prompts. Second, network visualization of a CONCOR analysis revealed four clusters: 'women's fashion and style,' 'men's fashion and style,' 'photorealistic shooting,' and 'fashion portrait.' It was also found that fashion prompts use words to generate photorealistic images and fashion portrait images containing elements of women's or men's fashion styles as well as elements of shooting. Although there are elements...