Text-mining metadata: What can titles tell us of the history of modern and contemporary art?

Abstract

The use of statistical text-mining to investigate the linguistic structure of textual resources has received limited attention in digital art history. In this paper the question I address is that of what text-mining titles as given in metadata can tell us about the history of modern and contemporary art. To investigate this question I constructed a dataset from the metadata for over 170,000 artworks, drawing on the online collections of 133 art museums in 30 countries. The use of topic modelling, parts-of-speech tagging and word counting allows me to identify large-scale and long-run patterns in the language used in the titles of those artworks. I set out an art historical reading of those patterns in which artistic interests signalled by the language used in titles come and go and are re-inflected, epistemic perspectives on the kinds of knowledge art can or should engender change, and artists engage with the ways that the title functions. My ‘distant’ reading is consistent with the canonical history of modern and contemporary art and cuts across the particularities of artist, period or movement which often feature in such accounts, providing a fresh perspective on that history. It also complements and extends the scholarship on the history of titles in the visual arts. The analytical framework and the dataset I have developed are not limited to answering the question addressed in this paper, and I consider some of the possibilities for future work.