The FASHION PARATEXT DATASET focuses on the collection and analysis of fashion captions within contemporary fashion media. Although often overseen and rendered subordinate, these paratextual snippets of text—such as titles, introductions and captions—work as strategic value producers within fashion media and shape our fashion narratives and vocabulary. Accordingly, these textual elements play an important role in our relation to fashion and clothes as readers, wearers, makers and consumers. Through its dominance and vast networks, industrial market-based fashion language is becoming our fashion mother tongue. And as professor of applied linguistics Robert B. Kaplan writes, our first language, or mother tongue has a powerful influence on the way we shape our thoughts and organise our ideas.

Using data science methods, this project collaboratively produces a large-scale dataset of fashion captions that can be mapped and analysed using Natural Language Processing. The dataset takes the captions out of the saturated pages of fashion media (both print and online), offering the opportunity to read them attentively, isolated from their original context. As such, it can open up space to think about an alternative vocabulary.

Project leads
Femke de Vries & Laura Gardner

Website & consultation
Rowan McNaught

Research volunteers
Charlotte Plumb, Charlotte Verdegaal, Julia Berg, Leanne Choi, Lianca Van Der Merwe, Lindy Boerman, and Yashna Seethiah.