Cultural Analytics Lab: Rachel Fredey/Jackson Graves

The Stanford Literary Lab is a significant undertaking that aims to identify various patterns within literature, and how those patterns connect to the audience. The site also aims to explain the experience of the reader within certain literary contexts. It examines variations of types of language use, such as poetic forms, taxonomy, and the use of feelings and emotions in a particular work. The projects start as experiments and end up in the form of published pamphlets. The projects collect a mass of data pertaining to one aspect of literature, such as the word space of tragic characters in Antigone. This data is then portrayed in bar graph or concept maps.

A cultural analytics project can be identified through its use of large amounts of data that is extracted from a work of cultural significance, whether literary or otherwise. That data is then organized, and processed in order to identify patterns, which may reveal truths or bring up further questions related to traditional assumptions on the subject. This information is visualized in an accessible and useful way.

We evaluated each project and website in  a few ways. First, how accessible and well laid out is the project? Is it easy to understand and follow? Does it present the information in an innovative or new way? In addition, we also considered the ultimate usefulness of the site. Why should I take the time to analyze this source through the site as opposed to interacting with it myself, directly? For example, I could read Sense and Sensibility on my own, or I could the utilize to understand linguistic trends within the book (CITE). Lev Manovich also points out that cultural analytics is a powerful tool for understanding a culture, through computation and visualization of large amounts of pertinent data. Ones understanding of an area of focus can shift from vague to “razor sharp and at the same time acquire a new depth” (2)

Determining the success and failure of a project seems almost intuitive, in a way.  A few examples of successful projects include the Chicago Road Planning Project, and the project related to use of color in visual representations. The Visualizing Data project on Chicago is successful because it has a blend of different media types. Text, color, maps, videos are all used to portray patterns, history, and information regarding Chicago urban planning (3). The second Visualizing Data Project explores different ways that color can be used to enhance the quality and usefulness of data visualization. This seems to be an effective technique, as shown in the various illustrations from the income of CEO’s to the health of a respiratory system. (4) Hyper History is the least effective of the bunch. (4.5) Its aesthetic is clunky and outdated, but it does use some form of color coding to organize itself, especially given the size of the site and the amount of material involved.

Here are some other examples of how diverse a form cultural analytics can appear in. The Archimedes Palimpset (5) creates a digitized version of Archimedes’ ancient manuscripts, which makes them far easier to read, interpret, and analyze. The Jane Austen (6) project uses large amounts of computation and statistics in order to allow the user to the frequency or uniqueness of every pattern in the text. Many other patterns are also analyzed, connecting the book on a new level. Digging into Global News (7) takes a different approach, analyzing the content of President Obama’s speeches in order to see patterns in body language, location, length of message, topics, etc. Katrina Commemoration (8) uses digital mapping to study and grasp patterns in commemorations around the state. People can submit, categorize, and tag their story within this context. These projects seemed to be focused on specific areas of content that can be understood more clearly through the use of cultural analytic.

 So, why should we care about cultural analytics? This is, in large part, the muscle that drives projects in the Digital Humanities. This is the means through which scholars can reconciliate the previously stark gap between data and humanities undertakings . The former can be used to engage with a work, idea, or topic in new, and most importantly, productive ways. As it rightly should, Cultural Analytics makes scholarship feel right at home in a century riddled with numbers and buttons.


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