Literature and Computation presents some of the most relevantly innovative recent approaches to literary practice, theory, and criticism as driven by computation and situated in digital environments. These approaches rely on automated analyses, but use them creatively, engage in text modeling but inform it with qualitative[ -interpretive] critical possibilities, and contribute to present-day platform culture in revolutionizing intermedial ways. While such new directions involve more and more sophisticated machine learning and artificial intelligence, they also mark a spectacular return of the (trans)human(istic) and of traditional-modern literary or urgent political, gender, and minority-related concerns and modes now addressed in ever subtler and more nuanced ways within human-computer interaction frameworks. Expanding the boundaries of literary and data studies, digital humanities, and electronic literature, the featured contributions unveil an emerging landscape of trailblazing practice and theoretical crossovers ready and able to spawn and/or chart the witness literature of our age and cultures.
Introduction and Chapter 3 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Literature and Computation. An Introduction
Chris Tanasescu
Part 1: Platform Intermediality
1. Dynamical Systems and Interplatform Intermediality. The Case of #GraphPoem
@ DHSI
Chris Tanasescu
2. Platform Intermediality. Rimbaud ZAP @ Abrüpt
Servanne Monjour and Nicolas Sauret
3. Reimagining Translation Anthologies. A Journey into Non-Linear
Computational Assemblages
Raluca Tanasescu
Part 2: Hermeneutic Modeling
4. Hermeneutic Modeling of Detail in Textual Zoom and Literary Texts
Florentina Armaselu
5. The Novels Factory of Opinions: adapting sentiment-analysis tools to
ELTeC prefaces
Ioana Galleron, Roxana Patras, Rosario Arias, Javier Fernández-Cruz,
Frédérique Mélanie-Becquet, and Olga Seminck
6. Reflective Modeling (Modeling what would be there). A critical, creative,
and constructive approach to data modeling
Jan-Erik Stange
Part 3: Analytical-creative Approaches
7. Writing like a Machine or Becoming an Algorithmic Subject
Johanna Drucker
8. The Shepherds of Electric Sheep: Generative AI and Creativity
Andrew Klobucar
Chris Tanasescu is a poet and academic with backgrounds in English and computer science. The Graph Poem project he started 15 years ago has outputted natural language processing and network science-based poetry classifiers, intermedia performances, and computationally assembled poetry anthologies. His alias MARGENTO refers to a cyber cross-artform ensemble and international coalition of poets-translators, visual artists/musicians, and coders throwing events and launching publications on and off-line in four continents. Chris is currently a research scientist on the PIETRA project at the University of Galway. Previous or ongoing positions and affiliations include Coordinator of Digital Humanities at the University of Ottawa, Altissia Chair in Digital Cultures and Ethics at Université Catholique de Louvain, Senior Researcher in Global Literary Studies and Complex Systems at Universitat Oberta de Catalunya, and Visiting Scholar at the Electronic Textual Cultures Lab, University of Victoria. He is an Asymptote Editor-at-Large.
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