Tag Archives: Twitter

Betty Who?: Social Media and the Construction of New Pop Celebrities

Link to project: Somebody loves this.

Overview: The basic premise of my digital essay is to explore the intersection of social media (specifically YouTube and Twitter) and proto-celebrities—those artists that are still relatively unknown but who already have a well-established, committed fanbase and the talent necessary to be “the next big thing.” On a more analytical/theoretical level, my digital essay explores how fans use social media and engage in digital participatory culture to construct celebrities from the bottom up—how we interpret, synthesize, produce, and disseminate texts, images, and meanings that surround our proto-celebrities of choice. I use Australian-born singer Betty Who as a case study to highlight how the digital mechanisms of participatory culture actually work by providing a close-reading of two specific online events related to her music: the viral video “Spencer’s Home Depot Marriage Proposal,” which features Betty’s debut single “Somebody Loves You,” and the release of her second EP Slow Dancing because of how her fans—the “Who Crew”—reacted to it on Twitter.

Process: This project developed, unlike some of the more “traditional” essays I’ve written as a graduate student, out of my passion for pop music, which I always thought didn’t have much of a place in the academy. I first began by collecting and synthesizing a wealth of scholarship that proved quite the opposite: that popular culture could very much be a valuable source of inquiry. The second part of my essay, entitled “Convergence Culture and Redefining Fandom” is essentially my trying to work through all of that source material and to create a theoretical framework.

Moreover, unlike most of the other essays I’ve written, the peer review process had a considerable impact on how I drafted and revised this project. Having to go through multiple peer review sessions forced me to take a more proactive approach with my writing process, whereas I normally would have left most of the drafting until very near to the final deadline.

Affordances: Although I would like to think that most of my digital essay could easily translate into a more traditional form(at), the fourth part entitled “The Twittersphere and the Who Crew” would not because of its reliance on the use of embedded tweets. By embedding those tweets into the body of the post, they become a much more participatory aspect of the essay, in that they provide important visual and verbal cues as well as enable readers to actively form a network between my blog and Twitter with a simple click, like so:

If I were to have written part four in a Word document, I would have had to reduce these tweets to static screen shots or worse, to summarize their content, neither of which would have had the same rhetorical impact.

Constraints: The one aspect of this project that I struggled with the most was, as Naghmeh aptly called it, its “digital flexibility.” I knew that a blog could be multimodal very easily, but I wasn’t sure how to achieve such multimodality without it looking contrived. In a way, then, I became overwhelmed by the sheer amount of the web’s affordances, feeling like I needed to include as many of them as I could. But as the “final” version of my digital essay shows, I decided to use multimodality sparingly and to concentrate it mainly in my case study of Betty Who, which I felt was the place that needed it the most (rhetorically speaking).

After reflecting on my digital essay in this post, I want to try to offer some semblance of an answer to Joe’s question, “What changes when you write for the screen rather than the page?” As I stated above, I believe that writing for the screen enables us as writers to create projects that have a liveliness to them that writings for the page do not. Likewise, we can more (pro)actively create a network among our projects and the work of other scholars, bloggers, users, etc., in a digital environment, whereas simply citing or quoting in a static essay cannot or does not.

But I also don’t think that everything has to/does change when we write for the screen rather than the page, that we don’t have to adopt huge fundamental changes just to “fit in” with digital aesthetics and values, or to “look cool” as if we “get” what everyone is trying to do. To me, that feels incredibly disingenuous. We can write as academics on the web and use very few of its affordances (as I showed with Henry Jenkins’ blog in my post last week), or we can choose to be more conversational and creative—something I think Tumblr is really great for; it all depends on what each of us is comfortable with. And if a work is sound (read: effective, compelling), then why should it have to include multimedia just to grab our attention if that media isn’t going to add anything?

I’d like to conclude my post with the official music video for Betty Who’s song “Somebody Loves You.” It not only feels more apropos, given the subject of my digital essay, but watching it will also (hopefully) give you all a feel for who Betty Who is as we anticipate our arcade on Friday.

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“Mapping Twitter Topic Networks” and Tweetku Digital Essay

As I’ve been working on my digital essay, one thing I’ve been struggling with is how to show what the #tweetku community, or any hashtag community, looks like, without forcing readers to go experience for themselves.

I could try to depict this hashtag public by saying it has X number of contributors, or X number of tweets between Date A and B–but that doesn’t feel especially persuasive or meaningful. So, a portion of my research has been spent trying to figure out the best ways to incorporate and present quantitative data from social media sites.

The digital essay I want to contribute this week is a report on Twitter data visualization by Marc A. SmithLee RainieBen Shneiderman, and Itai Himelboim, entitled, “Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters.”

A quick summary: in an effort to better understand how Twitter political conversations happen, these guys analyzed many different conversations visually using software Node XL in order to recognize patterns:

Our approach combines analysis of the size and structure of the network and its sub-groups with analysis of the words, hashtags and URLs people use. Each person who contributes to a Twitter conversation is located in a specific position in the web of relationships among all participants in the conversation. Some people occupy rare positions in the network that suggest that they have special importance and power in the conversation.

What they found was that, through visual analysis, they were able to recognize at least six different kinds of network crowds.

  • The Polarized Crowd, which features “two big and dense groups that have little connection between them.”
  • The Tight Crowd, which is “highly interconnected.”
  • The Brand Cluster, which is made up of similar topic-driven commentary from many disconnected participants.
  • The Community Cluster, in which a popular topic has devolved into several, separate hubs of communication.
  • The Broadcast Cluster, in which “many people repeat what prominent news and media organizations tweet.”
  • The Support Network, which has a similar premise to the Broadcast Cluster except that the organization at the center or hub of the conversation is also replying and responding to many of its disconnected users (think of big business Twitter accounts that try to solve issues for their clients via Twitter).

Figure-3

 

This report has been extremely helpful for me in at least two ways: first, it gives me a set list of types of communities to compare #tweetku and other hashtag publics to, as well as ways of discussing the implications of being one of these community types. The #tweetku hashtag public, tiny as it is, is definitely a “Tight Crowd” community with many highly-interconnected members that all use the same or similar hashtags and respond to one another and with very few isolated members.

Second, this report gives me a better sense of methodology and resources–now that I know this kind of visualization is possible, I will be able to do it for myself. Unfortunately, Node XL is only available on Windows, so until I drag myself to the library for a day, I won’t be able to use that software.

Luckily, I’ve been able to find similar, if not quite as intensive, resources online. Using ScraperWiki, I’ve been able to get a lot of data–information about all of @TheTweetku’s followers, and information about every single tweet that includes the hashtag #tweetku or #tweetkuchallenge since April 22nd (unfortunately, it won’t let me look back farther than that).

With that information downloaded as a spreadsheet, I can then use Google Refine to clean up the data–fix it so that it catches all of the @mentions and #hashtags independently, cluster the locations together as much as possible, and edit it so I can export a new spreadsheet with only the necessary data.

Once I have that, I can use either Google Fusion Tables, Raw, or Gephi, to do the work of creating a visual element to display the data. Here’s what I’ve come up with so far:

  • A map of @TheTweetku followers

 

  • A look at the #tweetku community–the #hashtags (yellow) or @users (blue) involved, sized by frequency (this is visualization most similar to the original report–see the “Tight Crowd” interconnectedness?)

 

hashtagsvis

hashtagsvis (2)

 

  • A list of #hashtag publics associated with #tweetku, arranged by frequency

Although my attempts at data visualization aren’t anywhere near as grand as the report I’ve shared, I wouldn’t have known how to do them much less that they were possible without having read it. That’s a reason worth sharing, if nothing else.

Not Newness: Wherein I Don’t Say Anything Unexpected

Banks’ first moves threatened to drive me nuts. He posits, as many other eminent compositionists have, that we now live in a remix culture, and that this paradigm was launched by DJs. That scared me, as far as an assertion goes, because (as you all now know), my whole soapbox is: We have already, always lived in the RW, remix, intertextual culture, this paradigm is not new at all, perhaps only disrupted by the Enlightenment’s love of the image of the lonely artist operating in a vacuum to create works of sacred creativity. This is not new!

No doubt part of this is me taking pleasure in everyone else finally realizing, as I have in the course of accidentally becoming a genre theorist, that all writing is remixing (genre, after all, might be seen as a shared convention of what you remix from, with deviations/scratches being celebrated as innovation) and that the stodgy literary elitism of the past century (and this century still) has no legs left to stand on: it posits that remixes are inherently derivative, that genre texts are inherently inferior to the romantically-conceived, independent artiste writing a truly unique work of universalizeable and immortal literature, and this position simply cannot be sustained. Neither, really, can the laws that pretend it’s true. Just ask the RIAA.

Even if you literally show me pictures of myself writing my novel at 4am in a locked room, I will not buy the idea that there’s an un-remix-ed version of writing, or that this is new. There are novels in the room, and in my head, so no. Nope. No.

Nope.
Nope.

But then, within syllables, Banks saves himself (see page 2)–this is a book about locating African American cultural agency inside a paradigm that has suddenly returned to the fore after being mythologized out of modernity by a system built to construct African American as “other” (in the same way non-Enlightenment, non-European, “non-modern” groups get Othered to create the Us). The DJs hearken back to oral storytelling–the griots–meaning that this is not new, that this is just one way of looking at it that might be cool.

Digital Griots is a tool for reimagining what is going on–for scholars who have discovered the model in a new fashion, not an absolute pronunciation of the newness of the system itself. The DJ is “a figure through whom African American rhetoric can be reimagined in a new century” (2). The griot maintains the past within the present (see epigraph on 10), which of course makes the distinction really fuzzy. The way it ought to be.

That, at least, makes the academic in me happy. And it also helps to explain the really weird phenomenon that happened on Twitter–somehow, Tweetku has taken on a life of its own and has its own twitter, but we’re not sure if we made it or if we just happened to be doing the same thing while it was already there all along. Remix obfuscates historicity. The agent (the romantic author) blurs into the griot (the person speaking right now, the re-vision) (156).

My attempts, and our fixation, with locating an originator are probably possible but really counter to how the internet works structurally–the internet does not make allowances for the purity (and the myth) of the original. CNN’s silly attempts, every week, to find out about the source of viral things feels about as in-touch as their five weeks of coverage for a plane crash: they’re fixated on originators. Likewise, TV news networks talk about the hacker collective Anonymous as if it’s a thing, with leaders or consistent members. It is *not*. That’s the point. There’s no satisfying author at the end of the trail of remixes.

I did not make this image. It did not spring solely from me. I do not know who made it, and even if I did, it's an appropriation of another text.
I did not make this image. It did not spring solely from me. I do not know who made it, and even if I did, it’s an appropriation of another text.

That’s not to say that we shouldn’t protect remixers work, or reward particularly effective innovation, its just that we need to acknowledge that

  1. we’ve been doing that to certain remixers, called authors, but not to others,
  2. nobody operates in a vacuum (see the most recent presidential election’s key debate), and
  3. academic culture still creates systems of value, good or bad, around arbitrary distinctions between remix and original, derivative text and magical “springs fully formed from the head of the author, like Athena from Zeus” literature.
  4. Tweetku probably went viral somehow.

    This image is a pastiche of several memes, combined with a famous internet haiku. There are too many potential layered remixes here.
    This image is a pastiche of several memes, combined with a famous internet haiku. There are too many potential layered remixes here.

 

Twittering in the Wings: On Credentials and Institutional Compliance

While this is probably the textual equivalent of multitasking, I’m going to attempt to respond to Dr. Harris’ observations about critical discourse on twitter, since it actually has a lot to do with what I want to respond about regarding Fitzpatrick. This will all hopefully fit together in a moment.

As simple as it seems, I don’t think the technical allowances of Twitter allow for one-off critical discourse, particularly not when that critical discourse is actually critical. It’s easy to say, on Twitter, that “I really like what this scholar is doing here bit.lylink #tweet #epic”, but rather intensely more challenging to compose a response which might take issue–as my own stilted interactions with Tom Standage show. It’s impossible to fit Joe’s sentiment about the big-name panel in a tweet, particularly when he needs to spend more time on careful wording than concision. “Big-Name Panel was so TEDIOUS #4c14 #yawn #probablyshunnedforever” is not a satisfactory critical response, but it’s impossible to say “Saw Big-Name Panel, which was well-selected, but disappointing. Want to know more about Panelist’s ideas on [Issue-at-Hand], particularly when it comes to [Academic Soap-Box Issue] #4c14 #bigname” without pulling a + or a “(1/2) (2/2)”, which simply wastes more precious characters and risks dissolution in the sea of hashtag-filtered responses.

The perpetual personal surveillance that Twitter builds in doesn’t help, as a person can find your tweet about them even if you didn’t @ them. Twitter is all credentialed gossip, but none of the gossip can stay gossip, and the credentials can quickly become an albatross.

Seems Legit.
Seems Legit.

Twitter seems built primarily for praise, forwarding, or snark. Academic publication, as Fitzpatrick frequently points out, is built for analogous, but strategically different aims (11). Rarely is our praise unqualified (see: all of our blog posts on every author), but academic forwarding, (genteel) snark, and idea development are key–which is precisely why the current academic publication system hardly works better for these purposes than Twitter. Joe can’t tweet that the big name panel was tedious in the same way he can’t really publish a book out of Duke University Press about how tedious the panel was entitled [Big Name Panelist] is Silly. The peers are watching, and the credentials are at stake. An uncareful move might make Joe’s economy of reputation go the way of the Russian actual economy–and thus, academic speech has developed both an “ethical obligation to listen” (43), a means of gatekeeping (Peer Reviewed Publications), and a discourse based more on precision and diplomacy than concision (which is wonderful, but also not suited to microblogging). (For more thoughts on publishing, see Katie’s x5 post and all the comments on it regarding a new system of credentialing, funding, and publication not wholly unlike some of Fitzpatrick’s suggestions).

Fitzpatrick points out that this existing system of credentializing is necessary but restrictive–for instance, the abuse of institutional sponsorship to propagate outdated ideologies is protected by this system–and a more Twitterian, algorithmically-based system is similarly restrictive “bean counting” (47) reminiscent of the disastrous evaluation policies of No Child Left Behind (collective shudder). The disqualification of these open systems wholesale–emblematic in the early-2000s institutional dismissal of Wikipedia even as that publication does not employ this system–is not unlike the myth of Read Only culture I mentioned last week: it is, as Fitzpatrick put it, an artifact of an obsolescence-phobic “political project aimed at intervening in contemporary public life, perhaps with the intent of shoring up a waning cultural hierarchy” (2).

That’s why I’m glad Fitzpatrick gestured towards hybrid systems–while I still plan on writing monographs, it’s nice to think someday I might be able to write an article and put it out on the web for academics to read (since my field has no 100% applicable journal) and still have that publication “count.” Unlike Twitter, the web generally is not structured as to preclude academic forms of writing, and the fact that we tend to ignore that potential institutionally is disappointing. If the academic publication industry is a “zombie” system, shuffling along in an unsustainable fashion, academic writing in *form* and *aim* is less a zombie than (oh boy here we go) a cyborg–something not necessarily integrated with current technology that might be enhanced or reformulated to include it without particular difficulty.

Like the technophobic antagonists in every “Good Cyborg” story ever, though, we have to get over our institutional fear of this technology if we want it to work.

Official Tiny Leaves
Credentials: I Got ‘Em

My point, oddly, is this: the fact that Dr. Harris has no way to properly critique a panel for being tedious or nonproductive is already indicative of the serious problems facing not only academic discourse and publication, but the system of institutional influence and credentials that might allow the abuse of power by those who benefit from being able to be boring on big-name panels.

Case and point: last year I attended a conference on a prevailing issue in academia, and a very powerful, established academic (and Federal Funding magnet) gave a keynote speech on the issue. The speech was a tedious patchwork of outmoded ideology, institutional policy nonsense, statistics from the 1990s, and clearly-appropriated ideas on a series of projected slides. At the end, a room full of normally semi-revolutionary academic activists clapped.

Nobody said or tweeted a word.

Sentence Forming Nathan Fillion

Class, Fri, 3/07

Going Meta (1): Responses to responses [pdf]

Davidson, Now You See Itmooc-online-learning

Fastwrite: Take a few minutes to write a brief comment in reply to a post that you’d like to say something back to, but haven’t yet had time to do so. See if you can link your comment to a particular moment in Davidson’s text.

Going Meta (2): #685dw

x4: Concept in 60

Some examples

(Composed in English 211s, Duke University, Spring 2013)

iMovie 09 Basics

Thinking about Twitter

To do

  1. Tues, 3/04, 4:00 pm: Post x4, Concept in 60, to this site.
  2. Thurs, 3/06, 4:00 pm: Read Trubek and Rosen on Twitter.  Post at least one example of each of Trubek’s four types of tweets (headlines, questions, quips, responses) to #685dw.  If possible, try to do this work on Thursday, so these tweets are near the top of the feed.

Class, Fri, 2/14

Fastwrite

Rewarding/Frustrating/Funny: Describe a recent experience you’ve had with writing online that fits one of those categories. Use this story to introduce yourself to the class.

Introductions

Writing in a digital age

MachineUsingUsMichael Wesch, The Machine Is Us/ing Us

Near the end of his video essay, Wesch lists a number of terms and concepts he feels we’ll need to rethink in a digital age, including:

  • copyright
  • authorship
  • identity
  • ethics
  • aesthetics
  • rhetoric
  • privacy

Wesch composed and posted his essay in 2007. Pick one of the terms on his list and, in a fastwrite, see if you can point to some ways in which its meaning has shifted since then.

Aims and structure of this course

  • Rethink writing in a digital environment
  • Readings: Past, present, academic, teaching
  • Writings: Class blog and digital essay
  • Reading the schedule

Practical matters

  • Access to low-end digital photography, video, and audio
  • Deadlines, punctuality
  • Food
  • Laptops

x1: Responding to Baron

 Comments and tweets

Digital essaySelf Kafka's Wound

 Will Self, Kafka’s Wound (2012)

.

To do

  1. Tues, 2/18, 4:00 am: Read Baron. Post x1 to this site.
  2. Thurs, 2/20, 4:00 pm: Read x1s. Post comments to at least three.
  3. Thurs, 2/20, 4:00 pm: Tweet at least once to #685dw.
  4. Tues, 2/25,4:00 pm: Read Standage. Post x2 to this site.