A cloud representing a vector space model of words from over 1,300 French texts published between 1800 and 1899.
In his 1966 essay “Rhétorique et enseignement,” Gérard Genette observes that literary studies did not always emphasize the reading of texts. Before the end of the nineteenth century, the study of literature revolved around the art of writing. Texts were not objects to interpret but models to imitate. The study of literature emphasized elocutio, or style and the arrangement of words. With the rise of literary history, academic reading approached texts as objects to be explained. Students learned to read in order to write essays (dissertations) where they analyzed texts according to prescribed methods. This new way of studying literature stressed dispositio, or the organization of ideas.
Recent developments in information technology have challenged these paradigms for reading literature. Digital tools and resources allow for the study of large collections of texts using quantitative methods. Various computational methods of distant as well as close reading facilitate investigations into fundamental questions of the possibilities for literary creation. Technology has the potential for exploring inventio, or the finding of ideas that can be expressed through writing.
The Word Vector Text Modulator is an attempt to test if technology can foster inventio as a mode of reading. It is a Python script that makes use of vector space models of vocabularies mapped from a corpus of over 1,300 nineteenth-century documents in order to transform a text semantically according to how language was used within the corpus. An experiment such as this explores the potentiality of language as members of the Oulipo have done with techniques such as Jean Lescure’s S+7 method, Marcel Bénabou’s aphorism formulas and the ALAMO’s rimbaudelaire poems. With technology we can investigate not only how something was written and why it was written, but also what was possible to write given an historical linguistic context.
These aphorisms were generated with code developed by the Oulipo.
In the Atlas de littérature potentielle (1981, rev. 1988) the Oulipo mentions a number of experiments with computers as tools for exploring algorithmic constraints on writing. One example is the complete text of a computer program written by Paul Braffort that generates aphorisms (311-315). Today such programs are textbook exercises for learning computer languages, but Braffort wrote the program for a mainframe in the 1970s using the language APL (A Programming Language). Developed by Kenneth Iverson at IBM in the 1960s, APL is one of the earliest computer languages (after Fortran and Algol) designed to manipulate data as matrices. Although it is still in use by some programmers working in financial analysis, APL today is a fairly obscure language for which there are few compilers and interpreters.
In the 1981 edition of the Atlas Braffort extols the virtues of APL not only as a system of notations for formalizing literary structures but also as code that executes complex algorithms (113). Although he claims his computer program provides “a thoroughly complete analysis of the procedures used” to generate aphorisms, it needs to be executed in order to test the analysis and observe how the algorithms work. To this end I have transcribed the code published in the Atlas so that an APL interpreter can compile and execute it. The code is comprised of specific functions and pre-loaded variables. To run the code, you need to )LOAD this file into an APL interpreter such as APLX (there are other interpreters out there but APLX is the only one I have successfully installed in OSX and Ubuntu). At the prompt enter your name and the code will deliver an aphorism for each character you type (including the space between your first and last names).
If you manage to get the code to run, you may wish to understand how it works. For that I recommend APLX’s online tutorial.