I’m curious to explore what these three frames–technological, social, and physical–could offer in terms of different ways to understand and reveal DH labor in the academy.
“I don’t know a lot about philosophy,” says Grant Louis Oliveira, a data analyst and quantitative social sciences researcher with an undergraduate degree in political science. He continues:
I’d like to change that and more rigorously explore my ideas, but I find the world of philosophy a bit impenetrable, and I don’t think I’m the only one…So we need a map. What I imagined is something like a tree arranged down a timeline. More influential philosophers would be bigger nodes, and the size of the lines between the nodes would perhaps be variable by strength of influence. Of course strength of influence needs a metric, but we’ll get there. I know that Wikipedia pages for academics and thinkers tend to have a field for “Influenced by” and “Influenced”, and it struck me that we could use Wikipedia’s semantic companion dbpedia to build our little map.
And so that is what he did.
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The Renaissance Society of America is pleased to announce that it will partner with the Digital Humanities Summer Institute (DHSI) in 2016, to offer five tuition scholarships (each for one week) to current RSA members who wish to attend the institute.
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The Dietrich College of Humanities and Social Sciences at Carnegie Mellon University (CMU) is undertaking a long-term initiative to foster digital humanities research among its faculty, staff, and students. As part of this initiative, CMU seeks an experienced Developer to collaborate on cutting edge interdisciplinary projects. The Developer would work alongside researchers from Dietrich and elsewhere to plan and implement digital humanities projects, from statistical analyses of millions of legal documents to websites that crowdsource grammars of endangered languages. Located in the the Office of The Dean under CMU’s Digital Humanities Specialist, the developer will help start up faculty projects into functioning prototypes where they can acquire sustaining funding to hire specialists for more focused development.
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As the only historian in my immediate family, I’m responsible for our genealogy, saved in a massive GEDCOM file. Through the wonders of the web, I now manage quite the sprawling tree: over 100,000 people, hundreds of photos, thousands of census records & historical documents. The majority came from distant relations managing their own trees, with whom I share. Such a massive well-kept dataset is catnip for a digital humanist. I can analyze my family! The obvious first step is basic stats, like the most common last name (Aber), average number of kids (2), average age at death (56), or most-frequently named location (New York). As an American Jew, I wasn’t shocked to see New York as the most-common place name in the list. But I was unprepared for the second-most-common named location: Auschwitz. I’m lucky enough to write this because my great grandparents all left Europe before 1915. My grandparents don’t have tattoos on their arms or horror stories about concentration camps, though I’ve met survivors their age. I never felt so connected to The Holocaust, HaShoah, until I took time to explore the hundreds of branches of my family tree that simply stopped growing in the 1940s.
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I wanted to explore Spotify’s metadata in a way that would model the interpretive messiness of generic categories. To do so, I built a program that bounces through Spotify’s metadata to produce multiple readings of the idea of genre in relation to a particular artist. Spotify offers a fairly robust API, and there are a number of handy wrappers that make it easier to work with. I used a Python module called Spotipy for the material below, and you can find the code for my little genre experiment over on my GitHub page.
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After including the GenLit Project in my Experimental Writing course during the Fall 2014 semester, three senior undergraduates remained mesmerized by the perceived novelty of a generative, digital novel. For the following semester all four of us shared our frustrations, questions, and perplexities, which later drove our inquiry into the nature of the novel in its digital future. Many of those started as definitional questions around the confines of a novel while some others were reactionary, addressing why many are fearful of literature’s migration to digital platforms. As it turns out, much of the criticism we read to spur thought on our questions addressed materiality of the codex in conjunction with literature’s responses to digital technologies. We each read from a corpus of essays I chose and students augmented. With each week of reading we all wrote responses to the ideas we encountered, compiling and rearranging them as our collaborative essay developed. Each section of the essay had a “parent” author that worked to consolidate, develop, and edit more heavily than others in the group. This second installment of four catalogs four major traits of digital narratives we found in play with the Generative Literature Project. Beyond building a catalogue of traits, we compare the Generative Literature Project to other new media texts and look ahead to what this project may look like and how future readers might perceive it.
Traits of the Digital Narrative
The codex form is far from a stable state, but is instead a part of the evolution of humans externalizing their thought. The book is part of humanity’s “becoming,” but we’ve reached a stage where technological revolution, information, and the digital have overflown the book’s border. We don’t imagine the total encyclopedic book anymore, but are becoming more open to the idea of a linked, international prosumer who reads/writes on the Internet. The ready connection and cohabitation of words, image, and sound on the computer too no doubt engendered our increased awareness of the limited expressive capacity of linguistic signs printed on a codex page. Geoffrey Brusatto argues that digital media has altered how the reader interacts with the text. Now the digital reader handles information non-linearly and actively searches for specific information (295). The reader defines his or her own path in the reading and so is less of a passive consumer. This takes the reader (assumed to function by moving linearly through a text) and turns him or her into a user who navigates more like one travels through a dictionary. In fact, Ellen Lupton states that users want to feel “productive” rather than “contemplative” (295). This is an interesting binary. Are action and thinking then opposites? Perhaps we do both, and maybe a reading experience can exist on a sliding scale. Espen Aarseth has a sliding scale for narrative versus ludic features. Maybe we need to chart the novel based on reader action versus reader thought.
Read More: Can You Murder a Novel? Part 2