About this Project

With the rise of the digital humanities has come the promise of new methods of exploring literary texts on an unprecedented scale. How does our approach to literature and literary history change when the canon expands to include millions of texts—all of them immediately analyzable by cutting-edge methods? What previously undetectable trends, long-term shifts, and patterns within and across cultures are revealed when we study texts at this scale? Can software help us transcend language barriers to enable a truly global perspective for comparative literature? In recent years a diverse group of scholars at the University have taken up these research questions, exploring the possibilities and challenges that digital technology has introduced to the field of literary studies. The Textual Optics project brings these scholars together in a lab-like environment to consolidate and expand the scope of their work. The goal is to create a permanent home at the University for scholars pioneering this new approach to literary research.

The project centers on the concepts and practices associated with new scalable reading methods, many of which are imported from the sciences and enabled by recent software innovations—everything from data mining and visualization to machine learning and network analysis. The research team is employing a set of tools and interpretive methods that allow them to read textual archives through multiple lenses and scales of analysis, from single words up to millions of volumes. In particular, the project is considering how readers might move between close and distant readings of texts, alternating from a qualitative mode that involves traditional exegesis to a quantitative mode that involves extracting statistically significant patterns from huge amounts of data.

To date, this shift between modes has not been well understood. The most sophisticated software tools in this area focus more on the distant reading aspect of text analysis, and therefore create a disconnect between the results of the algorithmic processing of texts and the texts themselves. The abstraction afforded by distant reading risks erasing the particularities of cultural and intellectual production that humanists value so greatly. By integrating tools that enable high-level pattern detection in large corpora with more traditional philological methods of text analysis, the research team will develop a system of scalability that allows for both close reading and distant reading within a unified digital workspace. Textual Optics ultimately aims to demonstrate the value and extraordinary potential of literary scholarship at the intersection of computation and humanistic inquiry.

The potential of Textual Optics as a method largely depends on three components: a technical infrastructure that can facilitate the movement between distant and close reading; access to a wide range of corpora; and opportunities for scholars to work collaboratively on projects that cross linguistic and cultural domains. During the course of this project, the research team will leverage extensive technical experience in conceiving, developing, implementing, and using high-performance text analysis tools. Participants will produce a set of technical interfaces and models for digital literary study that expand access to this kind of work for humanities scholars and facilitate a critical awareness of where these methods stand in relation to other analytic frameworks. By creating a massive collection of digitized texts spanning multiple cultural and linguistic contexts and developing the tools and methods to extract insights from the data, the Textual Optics Lab will become a global destination for digital humanities scholars.

In its first year, the research team has been expanding an existing digital corpus by indexing into the University’s PhiloLogic search engine more than ten collections of texts in Chinese, English, and Japanese. Collaborators are also developing a text-reuse detection tool, which allows them to find reuses and borrowings of passages within large text collections. This helps scholars track intellectual and literary influence between authors within a given time period and from century to century. The group demonstrated the potential of this new tool at the University’s Digital Humanities Forum in May 2018, where they solicited feedback from colleagues and aimed to foster new collaborative partnerships. The team is also strengthening ties with scholars and institutions in China and France through close collaboration with Visiting Fellows Zhao Wei, Jean-Gabriel Ganascia, and Marine Riguet. Plans for a new initiative that will introduce undergraduate students to the concepts, tools, and methods being explored at the Textual Optics Lab are in development.

Image: "Giant" compound microscope of Descartes, courtesy Wellcome Images


What Can Big Data Teach Us about Eviction?

May 12, 2020

In an article in Public Books, Visiting Fellow Jo Guldi (a member of the Textual Optics research team) examined how data-mining can uncover new insights about eviction, the ways it reinforces structures of poverty, and Britain’s history of debating property rights. 


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