This project uses state-of-the-art machine learning techniques to study conceptual change over time. It builds on the seminal BERT infrastructure that has, in recent years, caused a breakthrough in the computational understanding of language. With the help of the Dutch National Library’s massive archive of historical newspapers, magazines and books, it is possible to show how Dutch words have changed their meaning and connotation in public discourse from the Second World War until the present day. The project aims to study the conceptual history of one of the most urgent issues of today: global sustainability.
In this project, we re-train the base model to create multiple, chronologically ordered models based on historical Dutch textual data. With the help of this technique, we will be able to trace continuities and breaks in this discourse to, ultimately, gain insights into the forces at play when it comes to sustainability.