This week’s readings raised a lot of questions about the connections between the humanities (especially literary and rhetoric studies), the sciences, and computer technology.

Ramsey’s Reading Machines explores the use of computer programs for text analyses in the humanities. He supports the increased use of computer technology in the humanities, but he expresses concern that the field is trying to mimic the sciences’ position with computer technology as a means to create an objective analysis. Humanists conducting text analyses must find a balance between the machine’s objectivity and the researcher’s subjectivity.

Thinking about the title as I read, I couldn’t help wonder who is the machine: the computer, the researcher, or both combined? By the end, I would say it’s both combined.

A topic in this book that particularly caught my interest was Mathew’s algorithm, a procedure designed to generate poems by “remap[ping] the data structure of a set of linguistic units (letters of words, lines of poems, paragraphs of novels) into a two-dimensional tabular array” (29).

The author shifts the characters in each row to form new words in the column, combines the new words, and this creates an unpredictable poem or story.

While reading about Mathew’s algorithm, I was reminded of Bogost’s Latour Litanizer, as described in his book Alien Phenomenology, and so I wanted to put Reading Machines in conversation with Object Oriented Ontology (OOO).

The Latour Litanizer creates a list of things (objects, people, events) by utilizing Wikipedia’s random page API.

For example, right now I’m generating a list through the Latour Litanizer (by simply clicking a button) and the product is

“The Sea Urchins, Cults: Faith, Healing and Coercion, Subhash, Roman Catholic Diocese of Limburg, Barber-Mulligan Farm, Charles Teversham, 2010-11 Belgian First Division (women’s football), Knox Presbyterian Church (Toronto), George Davidsohn.”

The list is designed to be random (at least in the confines of the algorithm, which may exclude repeats and more). Despite the randomness, I still form connections between the words. For example, Roman Catholic and Presbyterian Church (and some may argue cults) relate to religion and Limburg and Belgium are connected geographically.

On Bogost’s blog with the Latour Litany, he explains that this was created out of his curiosity of combining ontography and carpentry.

He describes ontography as “the techniques that reveal objects’ existence and relation” and carpentry as “the construction of artifacts that illustrate the perspectives of objects.”

The list puts things together than otherwise may never be linked, and we create relations from our knowledge and experiences. Therefore, the list may mean more to one person than another. Not only do we form or not form connections with the objects, they may form or not form connections with each other, although these connections are much harder to understand.

Although the Latour Litanizer seems more random that Mathew’s algorithm, both reveal new ways of read a text. They reveal connections (for example, Mathew’s algorithm revealed a prominent connection in form and the Latour Litany revealed the diversity of things humans deem worthy of having a Wikipedia page).

Whereas the Mathew’s algorithm may focus on a novel or a poem, the Latour Litanizer is constantly demonstrating new ways to read Wikipedia as a large body of text that represents society to some degree.

The Latour Litany is a unique example of a program that performs a text analysis of an entire website. It might not be the most productive exercise for researchers, but perhaps for distant reading, it could be useful for getting the bigger picture.