digital humanities ++ | Manovich's course at UCSD, spring 2011

One million manga pages

complete course syllabus: digital humanities++

Keywords: digital humanities, Calit2, UCSD, NEH, HIPerSpace, visualization, cultural analytics,, software studies, Lev Manovich

course description:

“How does the notion of scale affect humanities and social science research?
Now that scholars have access to huge repositories of digitized data—far more than they could read in a lifetime—what does that mean for research?”
The description of joint NEH/NSF Digging into Data competition (2009) organized by Office of Digital Humanities at the National Endowment of Humanities (the U.S. federal agency which funds humanities research).

“The next big idea in language, history and the arts? Data.”
New York Time, November 16, 2010.

Over the last few years, digital humanities - use of computational tools for cultural analysis - has been rapidly expanding, with growing number of grants, panels and presentations at conferences, and media coverage. (For example, New York Times is running a series of articles about digital humanities, with 5 articles already in print since November 2010.) However, most of the projects so far focused on text and spatial data (literature and history departments). With a few exceptions, other fields including art history, visual culture, film and media studies, musicology, and new media have yet to start using computational methods. But even in social sciences, the disciplines which are dealing with culture (media studies, cultural sociology, anthropology) and which employ quantitative methods, still did not discover full possibilities of "cultural computation." In short: the opportunities are wide open, and it is an exiting time to enter the field.

This graduate seminar explores the concepts, methods, and tools of computational cultural analysis, with a particular focus on the analysis of visual and interactive media. (This is also the focus of our lab's cultural analytics research).

We will discuss cultural, social and technical developments which gave us "large cultural data" (digitization by cultural institutions, social media) and which placed "information" and "data" in the center of contemporary social and economic life (the concepts of information society, network society, software society)

We will critically examine the fundamental paradigms developed by modern and contemporary societies to analyze patterns in data - statistics, visualization, data mining. This will help us to employ computational tools more reflexively. At the same time, the practical work with these tools will help us to better understand how they are used in society at large - the modes of thinking and inquiry they enable, their strengths and weaknesses, the often unexamined assumptions behind their use.
(This approach can be called reflexive digital humanities.)

We will discuss theoretical issues raised by computational cultural analysis: selecting data (single artifacts vs. sample vs. complete population); meanings vs. patterns; analyzing artifacts vs. analyzing cultural processes; methodologies for analyzing interactive media; combining established humanities methods with computational methods.

The course assumes that while computational methods can be used in the service of existing humanities questions and approaches, they also have radical potential to challenge existing concepts and research paradigms, and lead to new types of questions. To engage this potential, we have to start by considering "contemporary techniques of control, communication, representation, simulation, analysis, decision-making, memory, vision, writing, and interaction" enabled by software in society at larger. (Manovich, Introduction to Software Takes Command.) Projecting these techniques onto the problem of cultural analysis will tell us what digital humanities can be.

The seminar combines readings, discussion, exercises to learn tools and techniques, and collaborative work in groups to conduct original digital humanities projects. Students will be able to use any of the data sets already assembled by Software Studies Initiative (see examples) as well as the unique supervisualization HIPerSpace system.