Introduction

Remediation is a large field of study, which essentially covers two different directions of mediation: from literature to other media, and from other media into literature.

In the first case, the adaptation of literature into film is one example of remediation, setting music to poems is another, and making paintings with literary motifs is a third. One of the benefits of digitization is that it has become significantly easier to search for such connections between literature and the larger ecology of art that it has inspired.

The other direction of remediation, the inclusion of other media in literature, has seen less computational work. The understanding of front covers is one aspect of books’ use of other media, which calls for studies at scale (cf. Peter Leonard and Vogue covers). In electronic literature, the understanding of a text cannot be separated from an understanding of the underlying code that organizes the “plot.” Electronic literature is also a genre where several media converge: music, art, film, and the spoken word may be combined into one work, and calls for methods described in the entry on art.

Applications

Elementary

One simple exploratory approach is to make an image search in a search engine to find the most common images associated with a literary work. Try for instance to make an image search on Frankenstein, Animal Farm, or Dr. Jekyll and Mr. Hyde and explore the many different ways in which these literary works have been remediated - although some specific features tend to persist. You can also search film databases such as imdb.com for adaptations of a literary work. For instance, a search for Frankenstein’s monster at IMDb yields more than 300 suggestions.

Advanced

As film adaptations are a common way of remediating novels, one possible way to computationally analyse remediation is to investigate how loyal film manuscripts are to the original literary works. Classics such as Mary Shelley’s Frankenstein and Jane Austen’s Pride and Prejudice have seen many film adaptations throughout the years. Select a novel and a respective film manuscript, and look for parallel passages in them. For instance, the R package “textreuse” allows for detecting reuse in R. You can also use this script for text similarity as inspiration and write your own custom Python function to detect reuse. Count how big of a proportion of the film manuscript comes directly from the novel. 

A visual approach to remediation is to look at illustrations in books. To answer questions about their role and the changes in illustration trends, follow the Programming Historian’s tutorial on page illustration extraction and extract your image corpus. Focus on a genre or a period of time and carry out a visual investigation for its defining characteristics.

Resources

Scripts and sites

• R package textreuse to detect similarity and text reuse among documents.

• A Python script for detecting reuse in two texts.

• Programming Historian’s tutorial to extracting illustrated pages from digital libraries with Python.

Articles

• Chowdhury, T., Muhuri, S., Chakraborty, S., & Chakraborty, S. N. (2019). Analysis of adapted films and stories based on social network. IEEE Transactions on Computational Social Systems, 6(5), 858-869. https://doi.org/10.1109/TCSS.2019.2931721   
   
• Heyd, T. (2016). Digital genres and processes of remediation. The Routledge handbook of language and digital communication, 87, 102. https://www.routledge.com/The-Routledge-Handbook-of-Language-and-Digital-Communication/Georgakopoulou-Spilioti/p/book/9780367466459 

Arts »