I’m teaching a graduate-level class in Digital Storytelling at Brown this spring. You can view our course site here. Last week served as an introduction to three key terms and concepts that we’ll be working with all semester: data, networks, and visualizations.
Last summer I had the pleasure of attending HILT (for the second time!), where I completed a course on Database Design for Visualization and Analysis taught by Nicole Coleman. Nicole began the course with a great exercise that doubled as both an icebreaker and an introduction to some of the major ideas we’d be working with all week. Instead of throwing us headfirst into spreadsheets and digital tools, she split the class up into smaller groups and asked us to tell a story about our group in a hand-drawn visualization. This assignment inevitably involves the gathering of data and the questioning of what that data tells us, as well as what it might be used to tell others. It then quickly leads into a discussion of the benefits and drawbacks of visualizations, especially when you’re wrestling with a desire to retain more complex and varied dimensions of networks and relationships.
Our groups focused on commonalities as well as deviations. For example, I recall that one group was interested in mapping educational backgrounds geographically, in part because there were questions about whether digital scholarship was perhaps too localized and dominated by particular schools, programs, and regions of the world, and the group wanted to make visible the routes people took as students and emerging professionals. Some of these conversations could be difficult: they mapped “in crowds” and highlighted outliers and outsiders, they revealed certain investments in particular degrees, colleges, and career paths. They were also incomplete at times: a route might have ended or taken a turn in one direction due to personal reasons or professional obligations beyond a degree, for instance.
In any case, the exercise stuck with me, so I modified it slightly and brought it into our Digital Storytelling course. You’ll see what our class came up with below. A quick word before we dive in: I’m intentionally leaving the names of students out of this discussion, in part because it was course work in progress created without awareness of its potential digital afterlife, and in part because the students working on the visualizations varied thanks to the way Brown students “shop” for courses early in the semester (I have thoughts about “shopping,” but that’s another story). Future reflections on course work will explicitly credit particular students (and may, at times, be collaboratively written by them).
I decided to have students create an initial set of visualization and then re-visit (and re-visualize) their earlier work later in the week. Before the first set was created, students read “Network Theory, Plot Analysis” (Franco Moretti), “The Image of Absence: Archival Silence, Data Visualization, and James Hemings” (Lauren Klein) and “The Blackness of Meme Movement” (Laur M. Jackson). I chose these readings because they work with digital objects, tools, and methodologies to look at different kinds of data and networks and the stories they tell, as well as the stories they might be used to tell. Each author is also interested in what data, objects, and networks obscure or conceal as well as what they privilege.
On Tuesday, students were put into groups (there ended up being a total of three) and given fifteen minutes to create a visualization that told a story about their group. They were also encouraged to think about what data they might gather as well as how that data might be organized and gathered.
After class, I took photos of each whiteboard and uploaded these images to our class Dropbox folder. When we reconvened on Thursday, students had read “What’s Next? The Radical, Unrealized Potential of Digital Humanities”( Miriam Posner), “Notes Toward A Deformed Humanities” (Mark Sample), and “TXTual Practice” (Rita Raley). Before discussing the readings, we used them as prompts to distort, reimagine, and reshape Tuesday’s visualizations.
I’ve broken our course up into three major thematic concepts: distortion, curation, and transformation (you can learn why in my syllabus). Tuesday’s readings can all be tied to images and ideas of distortion in particular ways: Moretti finds himself arguably distorting Hamlet by abandoning the text to spend more time with his network illustrations, Klein looks at what metadata and data structures can conceal as much as reveal, and Jackson wants us to see and credit the blackness of many popular memes and think about “wherever blackness goes unaddressed” in discussions of memes and meme culture. Posner and Sample perhaps more explicitly focus on (and call for) more distortion, deformance, and weirdness in digital projects and practices, while Raley discusses a particular form of “distortion” (text messages writ large as projected images on the walls of building) and considers the ephemeral in an archive-obsessed atmosphere.
Without further ado, here are the visualizations and re-visualizations from our class sessions. I didn’t offer much in the way of particular checklists / questions to address, though I might consider the benefits and drawbacks of a more explicit and detailed set of instructions and reflection prompts.

On Tuesday, this group decided to inventory the apps each member had on his or her smart phone. It’s perhaps the cleanest and neatest visualization that was made during this session. We don’t have additional information about apps or users that might interest audiences: for example, the y-axis measures the number of group members by quantity, but we don’t learn much else about this group and who makes it up. We also talked about the additional data about app use available on their phones and how it was visualized and documented (I also mentioned how terrified my own data usage visualizations tend to make me when I’m close to my limit: I wonder how much thought goes into their frightening spikes and jags and what they are intended to motivate?).

On Thursday, this group reimagined its bar graphs and made effective use of brand logos to visualize additional information about data and data usage. Group members also began to consider whether or not the data contained in these applications was as readily “at their fingertips,” and they began to discuss the various project challenges (ethical and otherwise) that a larger-scale attempt to use social media data and bring in different kinds of data might inevitably encounter.

On Tuesday, this group was interested in how its members inhabited institutional and geographic regions in relation to Brown University, and so its visualizations reflect an initial and quick inventory of some of this data. Visualizations helped the group consider whether questions about distance and professional identity would be worth pursuing: for example, there was more to chew on when thinking about distance and enrollment date than there was when tracking who came from where (it’s a Public Humanities course, so it’s not too surprising to see so many Public Humanities students in the group). We also discussed the ways tools inevitably shape, and in this case limited, the visualization being created: a more precise rendering of geographic distance would separate these data points further than a sketch drawn quickly to fit on half of a whiteboard. More seriously, these kinds of limitations and the potential for the particularities of data to become flattened remain factors when considering visualizations created digitally: the limits of these tools may be less visible but nonetheless remain present.
Also, this group drew a donut to show that 100% of the group liked donuts.

On Thursday, this group decided to focus on an area it valued but didn’t take into account earlier in the week: the emotional distance between students and the university. As someone who has spent a long time thinking about emotional labor in digital and academic work, I loved this revision for considering this data and its difficulties. I loved the group’s visualization idea even more: they envisioned a digital interface that asked Brown community members to document their emotional ties to the college on a given day by placing an emoji somewhere on an image of Brown’s famous main Van Wickle gate. I would really like to see this visualization exercise happen, as I love the playful way it asks its audience to think about emotional labor. That being said, we also talked a bit about the logistics of both creating this interactive visualization and handling data. The data could tell an interesting story about the school when viewed across a long period of time, but the interest in the preservation of this data and context on its potential re-use should be clear to users (and these emphases may lead some users to not participate).

Our third group was initially interested in follower counts and Snapchat “scores” and how we might think about the relationship between age and attention we are paid / the attention we pay to particular social media platforms. They also committed to drawing little Snapchat ghosts, which was nice. We talked a bit about what we can and can’t tell from these metrics and how the publication / visibility of these numbers might impact frequency and form of use. For example, while Snapchat’s web site is vague on how it calculates its scores, users may still feel compelled to spend time on the app if the number noticeably increases or decreases.

This group also found time to make a Venn diagram of Facebook friendships. I found these numbers particularly fascinating, but possibly that’s because I don’t think I have 185 friends, let alone 185 mutual friends with someone else here at Brown. We talked a bit about what these numbers tell us about “friendship” and social capital in digital contexts. I also like that the larger Facebook universe (seven billion and counting) is part of the visualization, reminding us that these numbers may look small when compared to the larger network.

On Thursday, this group decided to reimagine Facebook activity in a manner that directly and dramatically brought the economics of attention to the forefront. Instead of focusing primarily on age and conventional stories about generation gaps re: technology, the group thought about how it might document the time “spent” on Facebook as time that is inevitably predicated upon a user’s relationship to capital. Here, Facebook’s “power” users are reimagined as individuals who have invested in that time in various ways. While the number of dollar signs don’t necessarily equate to particular numbers in this drafted visualization, this group found a dramatic visualization of economic difference to be a useful prompt for a conversation about what these symbols might signify: the cost of data usage and connectivity, the unbilled hours spent funding friendship acquisitions. And the decision to surround these “fund requests” with the familiar design of a Facebook page is an attempt to defamiliarize the site’s desire for a space for friends that isn’t described in these terms.
Questions? Comments? Please feel free to bug me on Twitter (@JimMc_Grath) or email me: james_mcgrath@brown.edu. For more information about Digital Storytelling, visit our course site (and stay tuned for updates as the class completes additional work)!.