It was the best of times and the worst of times for data academia this week, at least in my take on the articles. On the one hand, I found in the Robertson & Travaglia piece a really informative and concise overview of links between our ‘Big Data’ issues today and historical precedent in the 19th Century I hadn’t considered. The ‘Avalanche of Numbers’ fascinates me, and I’m surprised I hadn’t heard it specifically referred to before this point. I also appreciated the straightforward discussion on the perils of ‘deviant’ social categories in objective data, though of course that’s a topic that has haunted us since Week 1.
But what I enjoyed less, and therefore what will subsequently take up more of my attention, was “Understanding Social Media Logic.” Though I’m likely being a bit too hard on the article (polemics make better blog posts), I felt that while the four “grounding principles” might encompass a helpful tautology to serve as a starting point for a social media research project, overall they presented as curious choices to frame a discussion of social media ‘logic’ in relation to mass media logic.
Most simply put, I thought that both ‘programmability’ and ‘popularity’ both boiled down to human agency in a manner non-unique to social media. I don’t even think this was something obscured or manipulated for an unfair point—the article is straightforward that human agency is half of programming, and in the other half (technology) invokes Gillespie’s contention that in technical social media programming practice, human choices “have not vanished…[they] are processed imperceptibly and automatically” (6). Popularity, too, seems an almost-synonym for what’s already being discussed here, and I think the argument that the difference between social/mass media logic is that social media can measure popularity while also trying to influence it falls flat based on the direction of influence. The example here is that large groups of users can band together to influence popularity, but how is that any different from viewers of television programs or non-digital political activists (besides the higher efficiency of the social media platform)? There is a mention of platform owners using popularity to promote causes, but the given citation seems far more a textbook example of programming that could have existed on any broadcast news report from the last fifty years.
The final pillars (‘connectivity’ and ‘datafication’) seemed far more useful to me, but at this point I’m not sure about their framing and it seems the concepts might be mobilized more usefully in a different discussion. Especially considering the opening case study of the ridiculous behavior surrounding a teenager’s birthday party, the unpacking of these concepts as social media fallout could be handled far more specifically in relation to existing mass media logic.
How I’ll be dressed on Monday?
Though to be blunt I don’t really believe either article brought anything earth-shattering to the table this week, I at least enjoyed Vaidhyanathan’s piece on “The Googlization of Us.” (Castells’ essay, somewhat oddly written and with the most head-scratching references to date, reminded me more of a tautological text better suited for one of our undergraduate courses.) Vaidhyanathan’s look at Google’s strategic deployment of default choices and the enumeration of five basic privacy interface classifications made for interesting reading, though of course I do need to take one for my team and raise issue with his casual (and in this case quite literal) defamation of reality television as demonstrating “a positive relationship between the number of cameras and observers pointed at a subject and their willingness to act strangely and relinquish all pretensions of dignity” (595). While the last decade has been kind to my fair reality television’s seemingly eternal quest to earn a seat at the table of ‘legitimate’ media scholarship, we don’t need to look any farther than the audience at Dr. Patrice Petro’s talk last Tuesday (unquestionably loaded with academic all-stars) and their titters of laughter as The Bachelor and other reality shows were name-checked during the discussion. I concede that reality television has and continues to be home to ‘ordinary’ citizens behaving extraordinarily and at times almost certainly with an eye for the camera, but its positioning as a concrete example of Vaidhyanathan’s larger point here seems to me highly unfair.
Getting more to the point of the ‘cryptopticon,’ I was reminded of a New York Times article from a year ago about Justine Sacco, a communications director who offhandedly tweeted a stupid joke about Africa and AIDS to her 170 followers and then found herself the top worldwide trend on the site (http://www.nytimes.com/2015/02/15/magazine/how-one-stupid-tweet-ruined-justine-saccos-life.html?_r=0). The article, which I highly recommend, goes on to document other people who have becomes targets of public outrage over some controversial post, and describes in detail how they’ve lost their jobs and had their social lives destroyed. Most interesting though is the connection author Jon Ronson draws with America’s history of public shaming in the 18th and 19th centuries, writing that it thankfully fell out of favor because “well-meaning people, in a crowd, often take punishment too far.”
These cases interest me because I think they get to the root of what’s problematic about social media and internet privacy; while the role of institutions like Google and explicitly stated privacy policies are important, in my view the malice of the anonymous masses and their cruel manipulation of what becomes made public is far more sinister than the dispassionate commercial interests of Internet authorities. Whether or not I agree that Google has too much power, I hate the notion that information and opinions will of course be immediately attacked if made public has sadly become an unchallenged given.
pictured: me after most grad seminars
“There is no such thing as public opinion. There is only published opinion.” -Winston Churchill
Baudrillard’s meditation on “the forced silence of the masses in mass media” is an insightful if dense essay, but I found the example of public opinion polls somewhat blinkered given the scope of the topic. True, the vastness of the issue does necessitate specifics to stand in for the discipline at large, but especially given the topic of our seminar I kept coming back to the question of public opinion polls as data. Baudrillard hangs his hat on the idea that these polls and reality belong to two heterogeneous systems and predictably references that old chestnut regarding the nonexistence of a relationship between systems of meaning and simulation; where he hitches this nonexistence to the notion of opinion polls as simulation is where I find many additional avenues of inquiry that spring from such thinking.
The initial example I considered was the larger field of statistics, which Baudrillard gestures to and somewhat non-academically dismisses: “deep down, none of us believe in them.” Though his point regarding the “involuntary humor” of a consistent disregard of statistics is well taken, the root of that humor remains the incongruity between the usefulness of statistics as an objective indication of probability and the narcissism of the individual who regards his or herself as somehow exempt from and above such modeling. Put another way, it’s funny because we know we should follow those stats, and perhaps the counter to Baudrillard is that even deeper down, we all know we should believe in them but don’t anyway.
Certainly I think there’s far more to be said about statistics’ effort to bridge the gap between the two heterogeneous systems Baudrillard here identifies: the field drives major decisions with very real-world outcomes in almost every field, from politics to finance to sports and entertainment. Candidates drop out of races when poll numbers come in too low, stocks are traded on financial analysis that largely relies on probability, and athletes and entertainers have careers made or broken with their statistical performance, be it measures in batting average or film gross. I guess my larger itch here is that Baudrillard isolates an example that preys on a personal experience bias (perhaps the very same narcissism bias that he later laughs along with) wherein he focuses on how a system of opinion statistics presented via media feels divorced from an individual’s reception thereof, but it seems to me that of course a model of how the US population considers an issue will likely challenge my own individual perception, if only in the confrontation where not everyone agrees with me regardless of the majority opinion. I understand the value of Baudrillard wants to get at here in a consideration of what happens when unidirectionality bumps up against social issues in the media, and I do especially enjoy the ending in which he identifies a deep desire of the masses to transfer all responsibility outside themselves, but for me the essay reads more like an old man yelling at the evening news. I can get behind the rejection of all statistical data as useless simulation in an undergraduate philosophy class, but as a potential media scholar I see the both the baby and the bathwater thrown out via this discourse.
pictured: not a damn thing
Perhaps because I began with the provocative “Glitch Studies Manifesto,” I was really intrigued by the tension between linearity and interruption that seemed to pervade all of the readings (or should I say, media experiences) for the week. Menkma’s manifesto sets the table for this dichotomy most cleanly: “the dominant, continuing search for a noiseless channel [read: uninterrupted linearity] …has been—and will always be—no more than a regrettable, ill-fated dogma” because “flow cannot be understood without interruption.” This basic premise of championing the unexpected interruption immediately bore fruit when I moved on to the Vector editorial statement, what appears to be a traditional few paragraphs curiously ‘interrupted’ by an invitation to click an image and move to an interactive display for the actual statement. Within this interruption was another series of interruptions, as the words I entered soon revealed themselves as part of a larger hierarchy that if not completely linear is at least conceptually adjacent. My own agency allowed me to skip around the hierarchy in my exploration, shifting the tension to myself as the user to sink or swim in an interrupted statement.
The McKenzie Wark interview was the most intriguing piece to this puzzle in my opinion, as my read of Wark’s answers versus Melissa Gregg’s questions pointed to a shift in his view of the “vectoralists” in relation to the hackers from the publishing of his book ten years prior. Where the initial idea of A Hacker Manifesto seemed to echo Menkma’s same championing of understanding the interruption to understand the flow, I read Wark’s current answers as somewhat disinterested from that ideological position; Wark seems far more concerned with simply explaining the state of hacking in 2013 (and consistently pushing his anti-carbon agenda) than in championing it. The notion that hacking as the interruption of the “vectoralists’” linearity is beneficial has given way to a more distanced view of the situation as almost deterministic: “few hackers end up owning the rights to what they produce. They become part of the vectoral class. But apart from a lucky few, they end up working for someone else.” I wonder if ‘hacking’ has become too antiquated to be truly counterculture, the technological equivalent of children dressing up as hippies for Halloween. If hacking is now an accounted-for piece of the vectoral class, what is the next step?
“Death to the fascist insect that preys upon the life of the people!”
Because I’m interested in working with reality television, I was most intrigued by Lisa Gitelman’s discussion on the problems of ‘dataveillance,’ or the collection and usage of data from individuals regarding their identities and personal attributes. She questions the ethics of this process in our current age, citing Rita Raley’s examination of those who try to push back with online tools that inhibit the ubiquitous data mining of our contemporary Internet. In ‘Dataveillance and Counterveillance’ (Raley’s chapter in the book for which Gitelman provides the eponymous introduction piece), Raley unpacks the typical argument in favor of allowing passive data mining: a “personalized Internet” is only possible if our individual tastes and preferences are fair game for circulation, and “voluntarily surrendering personal information becomes the means by which social relations are established and collective entities supported” (125). The necessity of trading privacy for inclusion is certainly problematic, and I see it as a specific link to my interest in reality television shows wherein contestants formally trade their privacy (as well as their very power of self-representation) for the benefit of inclusion on a television show and potential financial gain. Raley then introduces the idea of a ‘superpanopticon’ which must necessarily exist to register our interpellation by databases; while this for her is a link to a discussion of ‘corpocracy’ and ‘cybernetic capitalism,’ I identify it for my purposes as a term to describe the reality show institution which mines identity and individual action to construct the desired narrative for commercial purposes.
Aiding my consideration of a show like Survivor as one such ‘superpanopticon,’ Raley cites Kevin D. Haggerty and Richard V. Ericson who posit that surveillance “operate[s] through processes of disassembling and reassembling. People are broken down into a series of discrete informational flows which are stabilized and captured according to pre-established classificatory criteria. They are then transported to centralized locations to be reassembled and combined in ways that serve institutional agendas” (127). This is a lengthy excerpt, but I find it so startlingly appropriate to describe how contestants can be treated on reality television shows like Survivor. Contestants’ thoughts and feelings are mined on location through individual interviews known as ‘confessionals,’ which are then transported to a central editing station to be assembled together at the whim of the producers. My initial project idea to explore Survivor confessional frequencies by episode and season draws from this notion (which I could not have stated so well before) that players are mere building blocks in a larger narrative, who can be highlighted or backgrounded as the show desires. After reading Gitelman’s caution regarding the ethics of dataveillance, though, I begin to wonder: Even if I can use the confessional data to learn and expose something about the superpanopticon of Survivor, am I still inescapably guilty of drawing on the identities and representations of others for the alleged benefit of collective knowledge?
“Purple” Kelly Shinn, infamous as one of the most under-edited contestants in Survivor history