The main thing I took away from these ethnography readings in light of my own project(s) centered around fanfiction is my positionality as a researcher and the role that ethics plays in that. I guess I can largely think on this along three main lines: access, position, and representation.
A few things struck me from the reading, in particular the messy boundaries (and lack thereof) between online and offline and the difficulty of mapping and bounding digital projects. These pose significant implications for conducting online research. For now, I was mainly thinking about how some of these readings are impacting how I look at my own research project.
Encountering the readings–Berlin’s Rhetoric and Reality and David Gold, Catherine L. Hobbs, and James A. Berlin’s “Writing Instruction in School and College English”–I was thinking about the role that history plays. As someone who is new to the discipline, the past few readings have been helpful at giving some definitions and names. And with a few of them under my belt, I can start making connections and noticing absences.
But more broadly, I was thinking of these histories along four different frameworks: as genealogy, progress story, hagiography, and catalog.
Until this semester, I had not encountered the term “postdemographic.” First hearing it, I assumed it referenced the more individuated way that data collection could take place, putting less emphasis on the demographic that one belonged to and more emphasis on individuals themselves and what they did. In a sense, this understadning approaches the term, but Rogers completes it: “Postdemographics could be thought of as the study of the data of social networking platforms, and in particular, how profiling is or may be performed” (153).
Rogers also stresses the shift from the “biopolitical” to the “info-political,” explaining a shift from embodied attributes, like age and race, to the information that these bodies generate and consume. This explains a shift in focus on the data. Though the sites of data collection are not necessarily limited to “social networking platforms,” these sites tend to abound and automatically collect the sorts of data that postdemographics focuses on: taste, pop culture influences, political leanings, groups, associations, and the way that these may line up with people that you know or interact with.
These are the curated ads and Amazon book recomendations. The “you-might-also-likes” and “people-who-liked-this-also-likeds.” In my case, an odd mix of books on wine, Zen philosophy, critical theory, composition theory, and research methods.
Rogers also notes that many of these spaces, particularly in platforms like Facebook, the space itself reaches out for us to detail our preferences and network our contacts and interests through pre-set categories like books and movies that we like or more open-ended notes. It wants our data, takes that data, and constructs our experience accordingly.
That, very roughly, introduces postdemographics.
Contrasting the postdemographic with demographic, I see a complication: how do demographics impact postdemographics? As the Pew research reports note, demographic issues, like age and gender, connect with who uses a platform. For example, Pinterist users tend to be women: 42% of women online users, compared with 12% of men. Also, wealth and access still play a role in usage, which are again traditional demographic categories.
These potential considerations have both ethical and practical implications. On the more ethical side, I think it forces us to look at the dangers of essentialism and the issues of representation. Demographics may have a link to postdemographics–with certain demographics tending to prefer certain media–but this trend does not necessary make a truism. It is just a trend. And when value judgements and hierarchies enter the equation, as the often do with taste, attention to the fragility and complications of trends becomes more important. One must check assumptions and sloppy reasoning all the more, as more potential connections get put on the table and our pattern-pushing brains have more to work with.
This points to larger issues of big data and postdemographic data more generally. Though “the garbage in garbage out” caveat is common when it comes to the data itself, it also has some connection to our interpretations. When making claims and synthesizing findings, research requires self-critical analysis of our own thinking and transparency in our reasoning. One can easily see connections that a correlation may draw, but as often noted, correlation does not equal causation.
In a similar way, similar interest does not mean similar postdemographic–or demographic. Just because I like Doc Martin doesn’t mean I like Dr. Who. And just because people who like classical music may have similar browsing habits, values, or memberships does not mean I do.
On the one hand, this is obvious. But its obviousness should not detract from its importance.
Something that rings through David Russell’s “Nineteenth Century Backgrounds” and Clay Spinuzzi’s All Edge and “Symmetry as Methodological Move” is the tension between specialization and openness.
For Russell, the changing demographic of students entering higher education and their educational needs and expectations created a conflict between more general education and the specialized training of a discipline. On the one extreme, outlines Russell, one has the elitist liberal arts curriculum, “a single required course, identical for all students, regardless of abilities, interests, or career paths” (37). In this model, departments were flexible, and each educator could change roles easily. Schools were small and communal.
This unified, homogeneous education broke down amid increased discipline-specific and technical needs, though vestiges sometimes remained–like Harvard’s “forensic system”–as a general writing requirement.
Often, this general requirement has seemed to gain power from serving some need, ranging from civic or moral formation in its early years to solving the 1970s literacy crisis more recently. Thus, a compromise often took place between the two extremes: a school empty of general requirements, and one with a substantial one. In Russell’s history discipline-specific training has seemed to push out much of the general requirement.
“There is a pleasure in the pathless woods,
There is a rapture on the lonely shore,
There is society, where none intrudes,
By the deep sea, and music in its roar:
I love not man the less, but Nature more,
From these our interviews, in which I steal
From all I may be, or have been before,
To mingle with the Universe, and feel
What I can ne’er express, yet cannot all conceal.”
-Lord Byron, Childe Harold’s Pilgrimage
Starting off a reflection about social media with a quote from Byron about the solitude of nature seems counter intuitive. A “society, where none intrudes” clashes with the usual rhetoric surrounding the networked culture of social media and the digital, and the “lonely shore” and “pathless woods” probably lacks WiFi–or broadband.
But bringing in Byron highlights the paradox of place that the Internet and digital technology brings. We are networked selves, accessing the Internet in multiple ways from multiple places or portals, as our physical self continues to take up space and air “irl.” And much like the narrative locales of Romantic poetry, many digital spaces are constructed and emergent. They may have a url pinning them down, just as Byron’s saga traces the physical geography of Southern Europe, but Byron’s textual place–his “pathless woods” and roaring sea–arrive at us in ephemeral language. They are authored locales.
While I want to get into more concrete considerations of method, I want to pause initially and consider what “space” or “community” constitutes the subject of Internet inquiry. More specifically, I think that the quality of born-digital space forces us to look at space as an ephemeral, emergent gathering, and this should affect our methods. As Richard Rogers argues in Digital Methods, our methods should “follow the medium.” For now, I want to reflect on what that medium is.
[T]hey fancied that they could detect in numbers, to a greater extent than in fire and earth and water, many analogues of what is and comes into being—such and such a property of number being justice, and such and such soul or mind , another opportunity , and similarly, more or less, with all the rest—and since they saw further that the properties and ratios of the musical scales are based on numbers, and since it seemed clear that all other things have their whole nature modeled upon numbers, and that numbers are the ultimate things in the whole physical universe.
-Aristotle, Metaphysics, Book 1, 985b
Much of what interests me in data mapping and data extraction in light of network maps, concept modeling, vector space modelling, etc., is that they are not only methods, but also metaphysics.
Dealing with a corpus is a bit like the Pre-Socratics trying to find the underlying something that comprises reality. The big ideas–or Big Idea–that connects or threads the works together. The corpus may have alcoves and pockets, islands and peninsulas, but unity and commonality exists. Patterns exist.
To be honest, I’m not quite sure what a map is. As a child, I loved treasure maps, drawing them on tea-stained, sepia-toned sheets of crinkled computer paper. In such maps, a trail meandered through fantastical landscapes populated motifs I gleaned from kids books and pirate stories, starting from an arbitrary place and ending on an ornate X.
“Here be dragons,” I wrote over some hills, not knowing the cartographic history of the term, when map makers slapped it on the page to mark the unknowns. Castles and giants, towns, and mysterious lagoons pockmarked page after page. Such maps had no correspondence to reality.
When I got a little older, I got more scientific. I buried boxes in the yard and mapped the terrain of trees and bushes to show where they were. In scouts, I used a compass and topographic map. Watching Discovery Channel with friends, I read weather maps, learning their shifting symbols of pressure topographies, wind speeds, and fronts. In video games and history books I mapped out terrains and countries, borderlands and battlefields–both “real” and imaginary. And in music, I traced out correspondences between piano keys, tones, scales, music notation, chord structures, and auditory landscapes–relying on ear or memory to get a sense for how a piece mapped out, how it layered and piled together in a shifting set of tonalities and rhythms, loosely laced with emotion and allusion.
In school and in play, maps have saturated much of my life. Some are clear geographies, others are fictions. Some are abstracted topographies and a spattering of symbols, meant to make meaning or filter out noise. Some–especially these days–are notes dashed on within-reach pads, “maps” of ideas made of messy lines and bubbles that may prove indecipherable after a few days.
Throughout this journey, though, maps have felt somewhat secondary. They are means or aids, not ends. But revisiting mapping in the reading this week, as a word and a practice, threw me straight back to those early years sitting out in my parent’s garden, using my knees as a makeshift desk, pencil in hand, pensively sketching one.
Along the banks of the Allegheny River on a tepid September day in 2009, a college freshman decided to read the complete works of Henry David Thoreau.
Needless to say, he never reached his goal.
Reading the entire corpus of an author is pretty difficult. Not only for the sheer volume it contains, but also for the access it requires, with some books relegated to expensive collections. It’s also a question of utility: Why read an entire author’s oeuvre, when you’ll probably forget most of it?
But in digital humanities, the use of technology allows a range of new practices–new “reading” and analysis–that makes this act a little more feasible. Franco Morretti’s “distant reading,” for example, can allow a scholar to sift through millions of texts, using different data-driven lenses to pry out patterns.
And while this ability to access large swaths of text is helpful in itself, technology can play with texts in other ways, highlighting certain words, collecting certain patterns, making visualizations. As Tanya Clemens points out, such methodologies “defamiliarize texts, making them unrecognizable in a way (putting them at a distance) that helps scholars identify features they might not otherwise have seen.” This defamiliarizing lies at the heart of literary scholarship, finding new ways to understand texts.
But for now, I want to get back to my freshman self, sitting on the riverbank, reading an old library book of Thoreau.
In forensic science, Locard’s exchange principle forms one of its bedrocks. Formulated by Edmond Locard (1877-1966), the principle is pretty direct: anytime a crime gets committed, an “exchange” takes place, with a criminal leaving some sort of physical evidence behind and taking some sort of evidence with him or her. Through circumspect observation and sound reasoning, the detective can follow the evidence to learn something about the crime, hopefully solving it.
Whether it’s a drop of blood, some soot and gravel, or a thread of hair, something gets left behind or taken away that links the participants to the event, evoking a story from the materiality of what took place. We can never move through the world as ghosts, untouched and untouching. We’re always producing data.