Critical Modelling of Extensive Literary Data is a collaboration between colleagues at the Australian National University (ANU) and at King’s Digital Lab (KDL), supported by the King’s College London Australia Partnership Seed Fund and Australian National University Global Research Partnership scheme, for the period 2019-22 (followed by a short extension in 2023 due to the COVID 19 pandemic disruptions).
The objective of the two teams was to share knowledge and skills around computational analysis of extensive literary data by reflecting upon initial findings from the ANU Reading at the Interface project, which gathered, enriched and curated millions of reviews of Australian literature between 2018 and 2022. This dataset was generated by querying a range of platforms (social media, newspaper, and academic) using AustLit records of works and authors of Australian literature in a range of “forms” (including children’s fiction, essays, novels, novellas, poetry and short stories) published between 1788 to 2018.
During this exploratory project, KDL and ANU experimented with machine learning and “critical modelling” methods to propose alternative interfaces to these reviews which would aim to connect philosophical, ethical, and political frameworks of the humanities to the formal and data-intensive requirements of computational modelling. The overall objective of the collaboration was to increase institutional alignment with respect to infrastructure capabilities (including human expertise and workflows) at the crossroads of software engineering and literary studies research processes. KDL deliverables include a set of notebooks that will be integrated in the Reading at the Interface platform to be launched in 2024.
Team
- Arianna Ciula KDL Research Software Analyst
- Katherine Bode Principal investigator
Partner institution
Keywords
- Machine Learning and AI