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Curating a MediaCommons Collection on Algorithms

screen capture

MediaCommons website screen capture: November 24, 2015

I was flattered a few months ago to be asked to develop a MediaCommons Field Guide survey on the general topic of algorithms. In consultation with (and following the sage advice of) the MediaCommons editorial team, I formulated the following question to be addressed by respondents:

What opportunities are available to influence the way algorithms are programmed, written, executed, and trusted?

This survey question seeks to explore ways that digital humanities pedagogy and praxis might influence, produce, direct, or capitalize on the automated activities of algorithms. As algorithms seek to more intelligently predict what we might like using profile data mined from our archived and ongoing online activities, how might our access to ideas and experiences may be limited or expanded by the predictive power of self-learning algorithm-based decisions? Will our access to and ability to explore the vast range of opportunities available to us be enhanced, or will the predictive authority of algorithms reshape the landscape and horizons of our existence? Might the predictions algorithms make prove so accurate that we have little need to see or experience beyond the horizons shaped by algorithms? Contrastingly, are there positive implications for the ways in which algorithms shape our various digital experiences? The question encompasses composing or running an algorithm along with the results of algorithmic activity.

Responses may explore any aspect of the question; some possible approaches include:

  • The role(s) of algorithms in the digital humanities
  • Ways algorithms are involved in communication
  • (Dis)connections between artificial and human intelligences
  • Coding ethical algorithms
  • Influences of algorithms on humanistic pursuits
  • Computer games as algorithmic praxis
  • “Hidden” and/or “visible” algorithms that influence human activity
  • Algorithms, surveillance, and privacy
  • Government and corporate interest/investment in algorithms
  • Big data, data analysis, algorithms and humanities research

I reached out to a wide range of colleagues, friends, acquaintances, and heroes of scholarship I’ve encountered in my doctoral studies and asked for 600± word responses to this question.

The response and results are exceeding my wildest expectations. Responses to my email requests for contributions were greeted with warmth and encouragement. Those who were unable to contribute made their apologies with grace and recommended other scholars I might consider contacting to request contributions. I followed up with those scholars, too, who turned out to be as warm and receptive as the first round of respondents; several of them, in turn, contributed to the project. The experience of requesting contributions has been pleasant, as has the process of collecting those contributions and getting them posted.

I’m currently in the process of curating the collection of contributions, encouraging conversations and engaging other scholars in the dialogue that’s emerging around these posts. You can join the conversation at MediaCommons. I’m taking this opportunity to share with you what’s out there and to encourage you to join the conversation. More posts are coming after the Thanksgiving holiday, when I’ll add a post to include them.

  1. Curator’s Introduction: Organisms in a World of Algorithms — Daniel Hocutt, University of Richmond & Old Dominion University
  2. Algorithms and Rhetorical Agency — Chris Ingraham, North Carolina State University
  3. The Essential Context: Theorizing the Coming Out Narrative as a Set of (Big) Data — Marc Ouellette, Old Dominion University
  4. Algorithmic Discrimination in Online Spaces — Estee Beck, UT-Arlington
  5. Toward Ambient Algorithms — Sean Contrey, Syracuse University
  6. How Will Near Future Writing Technologies Influence Teaching and Learning in Writing? — Bill Hart-Davidson, Michigan State University
  7. algorithms at the seam: machines reading humans +/- — Carl Whithaus, UC Davis
  8. How Are We Tracked Once We Press Play? Algorithmic Data Mining in Casual Video Games — Stephanie Vie, University of Central Florida
  9. Crowdsourcing Out the Sophistic Algorithms: An Ancient View — Walt Stevenson, University of Richmond

If you’re interested in the way algorithms are being used across a variety of fields, disciplines, industries, and situations, you will find something interesting among the posts in this collection. These contributions are intended to generate conversation — I hope you’ll read one or more and join the conversation. I can attest that the scholars whose contributions you’ll be reading are approachable and more than willing to enter into dialogue.

Curating a MediaCommons Collection on Algorithms

screen capture

MediaCommons website screen capture: November 24, 2015

I was flattered a few months ago to be asked to develop a MediaCommons Field Guide survey on the general topic of algorithms. In consultation with (and following the sage advice of) the MediaCommons editorial team, I formulated the following question to be addressed by respondents:

What opportunities are available to influence the way algorithms are programmed, written, executed, and trusted?

This survey question seeks to explore ways that digital humanities pedagogy and praxis might influence, produce, direct, or capitalize on the automated activities of algorithms. As algorithms seek to more intelligently predict what we might like using profile data mined from our archived and ongoing online activities, how might our access to ideas and experiences may be limited or expanded by the predictive power of self-learning algorithm-based decisions? Will our access to and ability to explore the vast range of opportunities available to us be enhanced, or will the predictive authority of algorithms reshape the landscape and horizons of our existence? Might the predictions algorithms make prove so accurate that we have little need to see or experience beyond the horizons shaped by algorithms? Contrastingly, are there positive implications for the ways in which algorithms shape our various digital experiences? The question encompasses composing or running an algorithm along with the results of algorithmic activity.

Responses may explore any aspect of the question; some possible approaches include:

  • The role(s) of algorithms in the digital humanities
  • Ways algorithms are involved in communication
  • (Dis)connections between artificial and human intelligences
  • Coding ethical algorithms
  • Influences of algorithms on humanistic pursuits
  • Computer games as algorithmic praxis
  • “Hidden” and/or “visible” algorithms that influence human activity
  • Algorithms, surveillance, and privacy
  • Government and corporate interest/investment in algorithms
  • Big data, data analysis, algorithms and humanities research

I reached out to a wide range of colleagues, friends, acquaintances, and heroes of scholarship I’ve encountered in my doctoral studies and asked for 600± word responses to this question.

The response and results are exceeding my wildest expectations. Responses to my email requests for contributions were greeted with warmth and encouragement. Those who were unable to contribute made their apologies with grace and recommended other scholars I might consider contacting to request contributions. I followed up with those scholars, too, who turned out to be as warm and receptive as the first round of respondents; several of them, in turn, contributed to the project. The experience of requesting contributions has been pleasant, as has the process of collecting those contributions and getting them posted.

I’m currently in the process of curating the collection of contributions, encouraging conversations and engaging other scholars in the dialogue that’s emerging around these posts. You can join the conversation at MediaCommons. I’m taking this opportunity to share with you what’s out there and to encourage you to join the conversation. More posts are coming after the Thanksgiving holiday, when I’ll add a post to include them.

  1. Curator’s Introduction: Organisms in a World of Algorithms — Daniel Hocutt, University of Richmond & Old Dominion University
  2. Algorithms and Rhetorical Agency — Chris Ingraham, North Carolina State University
  3. The Essential Context: Theorizing the Coming Out Narrative as a Set of (Big) Data — Marc Ouellette, Old Dominion University
  4. Algorithmic Discrimination in Online Spaces — Estee Beck, UT-Arlington
  5. Toward Ambient Algorithms — Sean Contrey, Syracuse University
  6. How Will Near Future Writing Technologies Influence Teaching and Learning in Writing? — Bill Hart-Davidson, Michigan State University
  7. algorithms at the seam: machines reading humans +/- — Carl Whithaus, UC Davis
  8. How Are We Tracked Once We Press Play? Algorithmic Data Mining in Casual Video Games — Stephanie Vie, University of Central Florida
  9. Crowdsourcing Out the Sophistic Algorithms: An Ancient View — Walt Stevenson, University of Richmond

If you’re interested in the way algorithms are being used across a variety of fields, disciplines, industries, and situations, you will find something interesting among the posts in this collection. These contributions are intended to generate conversation — I hope you’ll read one or more and join the conversation. I can attest that the scholars whose contributions you’ll be reading are approachable and more than willing to enter into dialogue.

Rhetoric of Email and Text Messages in Cases of Rape

Trigger warning: This post addresses acquaintance rape and victim blaming.

I read this February 17 Chronicle of Higher Education article with interest about the use of texts and emails in rape cases, especially the bit about facing the “court of public opinion”: In Rape Cases, Students’ Texts and Emails Face the Court of Public Opinion. The title caught my attention because I was curious about the rhetorical use and purpose of those texts and emails — and especially who the sender of the messages was, the victim or the defendant.

Here’s how the article framed the issue:

Because of the nature of the crime, campus rape cases can be complicated for colleges to adjudicate. In the absence of witnesses or physical evidence, determining whether an accused student is responsible is often a matter of weighing one party’s word against another’s.

But what happens when the words they exchanged privately — emails or texts or Facebook messages, for example — are posted online for anyone to see?

In recent weeks, national news outlets have published two accounts of campus rape cases that drew on the individuals’ electronic correspondence, before and after the alleged rape, in an effort to characterize their relationships.

The article title suggests that the “texts and emails” faced the court of public opinion, but of course what the article is really reporting — what the article writers are really reporting — is that electronic conversations between the defendant and the victim, both before and after the rape, were released or uncovered in public spaces by national news outlets in reports about these two cases.

I’m focusing on the human agents and the words, rather than the medium and the location, as I engage with this text because I think the article too quickly objectifies both the messages and the humans in the story. And to be clear, the victim is the only one really “fac[ing] the court of public opinion” in this article.

The defendant is not facing that same court of public opinion. At least, the defendant’s words are not really the issue. Maybe, if the relationship had been verbally abusive in public, there might be reason to use those words against the defendant. But if we take this article at face value, the defendant’s words are not really the ones being weighed. The victim’s words are. The only quoted words in the article from any of those texts or emails are those sent by a victim “more than a month after the incident” that read, “I love you Paul. Where are you?!?!?!?!”

The article writers explain the presence of a victim’s words with this paragraph:

As the two cases illustrate, private statements can be used to support vastly different interpretations of an incident—or a relationship. Further complicating matters is that dealing with the aftermath of a traumatic episode can cause a victim’s behavior to seem erratic.

As readers, we are limited to two options for understanding these words:

  • They represent a relationship that is healthy and could not possibly be related to an abusive relationship of rape, OR
  • They are evidence of the erratic behavior of the victim.

As I read and reread this piece, I am amazed that the authors actually wrote “dealing with the aftermath of a traumatic episode can cause a victim’s behavior to seem erratic.” Because the consequence is that we must either consider the victim a liar or as a person behaving erratically.

Not as a victim of rape.

Not as someone who has suffered.

Not as a person.

Not as a human.

This is the consequence of binary thinking, of framing our understanding of an issue within dichotomous, or even semi-dichotomous, options. We limit ourselves to thinking in programmatic dichotomies, like if/then statements, rather than in complex, nuanced human terms. We objectify those who are in desperate need of being recognized as human and hurting.

The article concluded with the following quotes, which so anger me that I can hardly think straight.

It would be “remarkably irresponsible” not to consider digital communication between a victim and a perpetrator in a hearing, says Allyson Kurker, a lawyer who helps colleges investigate sexual-assault complaints. But not all digital communication can be given the same weight, she says.

“I’ve seen text messages exchanged very, very soon after an alleged assault, and I put less weight onto those,” she says. If a woman is saying things like “It’s OK” or “I’m fine,” says Ms. Kurker, “they don’t mean anything except the person just doesn’t want to deal with the situation right now.”

But if, weeks on, the alleged victim is sending friendly texts to the alleged perpetrator, that could mean something different. “It doesn’t make sense,” she says, “that they would be exchanging flirty text messages after that time if something had gone wrong.”

As I read Kurker’s words, there are only two conclusions the court of public opinion can draw when attempting to reconstruct the impossibly complicated rhetorical exigence that produced conversations between defendant and victim: Victims are either lying or flirting.

  • If victims say “It’s OK” or “I’m fine” immediately after the rape, either they weren’t raped (so they lied about being raped) or they were raped and they aren’t really okay (so they are lying).
  • If victims are “exchanging flirty messages” with a defendant weeks after the rape, either they are actually flirting and weren’t raped (so they lied about being raped) or they were raped and they are acting erratic (meaning they are living a lie).

Kurker’s closing words are deeply disturbing. In essence, by flirting, maybe acting as if everything is normal weeks after a rape, the victim is demonstrating that the rape could not have taken place.

If you have ever met someone who has been raped by an acquaintance or someone known to the victim, I challenge you to find evidence that the relationship is not being presented as anything but normal — and yes, maybe even flirty. When a victim knows the rapist, when the rapist and the victim have an existing relationship, how can we possibly expect anything but attempts to maintain some sense of normalcy?

That’s not erratic behavior. That’s survival. And a victim should not be indicted for surviving.

Rhetoric of Email and Text Messages in Cases of Rape

Trigger warning: This post addresses acquaintance rape and victim blaming.

I read this February 17 Chronicle of Higher Education article with interest about the use of texts and emails in rape cases, especially the bit about facing the “court of public opinion”: In Rape Cases, Students’ Texts and Emails Face the Court of Public Opinion. The title caught my attention because I was curious about the rhetorical use and purpose of those texts and emails — and especially who the sender of the messages was, the victim or the defendant.

Here’s how the article framed the issue:

Because of the nature of the crime, campus rape cases can be complicated for colleges to adjudicate. In the absence of witnesses or physical evidence, determining whether an accused student is responsible is often a matter of weighing one party’s word against another’s.

But what happens when the words they exchanged privately — emails or texts or Facebook messages, for example — are posted online for anyone to see?

In recent weeks, national news outlets have published two accounts of campus rape cases that drew on the individuals’ electronic correspondence, before and after the alleged rape, in an effort to characterize their relationships.

The article title suggests that the “texts and emails” faced the court of public opinion, but of course what the article is really reporting — what the article writers are really reporting — is that electronic conversations between the defendant and the victim, both before and after the rape, were released or uncovered in public spaces by national news outlets in reports about these two cases.

I’m focusing on the human agents and the words, rather than the medium and the location, as I engage with this text because I think the article too quickly objectifies both the messages and the humans in the story. And to be clear, the victim is the only one really “fac[ing] the court of public opinion” in this article.

The defendant is not facing that same court of public opinion. At least, the defendant’s words are not really the issue. Maybe, if the relationship had been verbally abusive in public, there might be reason to use those words against the defendant. But if we take this article at face value, the defendant’s words are not really the ones being weighed. The victim’s words are. The only quoted words in the article from any of those texts or emails are those sent by a victim “more than a month after the incident” that read, “I love you Paul. Where are you?!?!?!?!”

The article writers explain the presence of a victim’s words with this paragraph:

As the two cases illustrate, private statements can be used to support vastly different interpretations of an incident—or a relationship. Further complicating matters is that dealing with the aftermath of a traumatic episode can cause a victim’s behavior to seem erratic.

As readers, we are limited to two options for understanding these words:

  • They represent a relationship that is healthy and could not possibly be related to an abusive relationship of rape, OR
  • They are evidence of the erratic behavior of the victim.

As I read and reread this piece, I am amazed that the authors actually wrote “dealing with the aftermath of a traumatic episode can cause a victim’s behavior to seem erratic.” Because the consequence is that we must either consider the victim a liar or as a person behaving erratically.

Not as a victim of rape.

Not as someone who has suffered.

Not as a person.

Not as a human.

This is the consequence of binary thinking, of framing our understanding of an issue within dichotomous, or even semi-dichotomous, options. We limit ourselves to thinking in programmatic dichotomies, like if/then statements, rather than in complex, nuanced human terms. We objectify those who are in desperate need of being recognized as human and hurting.

The article concluded with the following quotes, which so anger me that I can hardly think straight.

It would be “remarkably irresponsible” not to consider digital communication between a victim and a perpetrator in a hearing, says Allyson Kurker, a lawyer who helps colleges investigate sexual-assault complaints. But not all digital communication can be given the same weight, she says.

“I’ve seen text messages exchanged very, very soon after an alleged assault, and I put less weight onto those,” she says. If a woman is saying things like “It’s OK” or “I’m fine,” says Ms. Kurker, “they don’t mean anything except the person just doesn’t want to deal with the situation right now.”

But if, weeks on, the alleged victim is sending friendly texts to the alleged perpetrator, that could mean something different. “It doesn’t make sense,” she says, “that they would be exchanging flirty text messages after that time if something had gone wrong.”

As I read Kurker’s words, there are only two conclusions the court of public opinion can draw when attempting to reconstruct the impossibly complicated rhetorical exigence that produced conversations between defendant and victim: Victims are either lying or flirting.

  • If victims say “It’s OK” or “I’m fine” immediately after the rape, either they weren’t raped (so they lied about being raped) or they were raped and they aren’t really okay (so they are lying).
  • If victims are “exchanging flirty messages” with a defendant weeks after the rape, either they are actually flirting and weren’t raped (so they lied about being raped) or they were raped and they are acting erratic (meaning they are living a lie).

Kurker’s closing words are deeply disturbing. In essence, by flirting, maybe acting as if everything is normal weeks after a rape, the victim is demonstrating that the rape could not have taken place.

If you have ever met someone who has been raped by an acquaintance or someone known to the victim, I challenge you to find evidence that the relationship is not being presented as anything but normal — and yes, maybe even flirty. When a victim knows the rapist, when the rapist and the victim have an existing relationship, how can we possibly expect anything but attempts to maintain some sense of normalcy?

That’s not erratic behavior. That’s survival. And a victim should not be indicted for surviving.

Southwest Popular/American Culture Association Conference Roundup

I’m returning from the Southwest Popular/American Culture Association (SWPACA) conference in Albuquerque, New Mexico. It’s my first time to this conference, the first time to New Mexico, and the first time to present a paper since my master’s degree days. I’m pleased to report that my paper presentation went well, although I think I excelled more as a panel chair than as a paper presenter. Never mind. I’m fortunate to have skill sets for both.

My paper, Boundary Crossings: (T)here Lies the Trickster, proposed the mythological trickster construct as a contemporary boundary object, synthesizing the boundary object definitions of Star and Griesemer (1989), Popham (2005), and Wilson & Herndl (2007). I used a class I proposed and taught called “Tracking Contemporary Trickster” as a case study demonstrating the benefit that using a trickster lens as boundary object has on the way students see the world.

In a sense this was a remarkably interdisciplinary paper. Although I presented it in one of the Myth and Fairy Tales panels, my topic connected to mythology only in that it used the trickster, a character that appears in many mythologies, as my object of study. My critical approach was application of professional and technical composition theory (the boundary object), while my case study involved pedagogy.

My experience suggests that this interdisciplinarity is the conference’s strength. The conference ethos is deeply accepting and encouraging, and represents, with few exceptions, an invitational rather than persuasive rhetoric. Presentations were not about presenting claims and theories as fact, but were instead aimed at capturing ideas and sharing them with others for consideration and feedback. Post-presentation comments were not about tearing down or critiquing arguments, but about praising areas of strength and offering suggestions for continued, further, or parallel research work. Interdisciplinarity appeared to be encouraged and appreciated, with a range of critical approaches and methods accepted and valued. More importantly, individual presenters were valued, an ethos handed down in large part, as I observed, by the panel chairs.

That said, I didn’t actually find my research niche during the conference. I guess I wasn’t really looking for a niche, but I found several of my ODU colleagues gravitating toward areas of study and consecutive panels in the same areas. Game studies was a very popular strand throughout the conference, and the networking and collegiality of the group was obvious and warm, even inviting to non-games people who were willing to listen and observe. As I seek to further refine my research agenda, particularly in the realm of the intersection of technology and rhetoric, I found the games studies researchers and scholars the most akin to my imagined future work. Digital games are spaces where technology and rhetoric intersect deeply and successfully, as are, perhaps to a lesser extent, classrooms. The parallels between classroom and game are striking and intriguing; there’s a strong case to be made (by Maury Brown or Megan McKittrick and other ODU games scholars, I think) that the classroom itself is game space, or can be conceived of as game space.

A brief chat with Marc Ouellette about indexical signs and algorithmic rhetoric was intriguing. Ouellette shared that he is interested in questions surrounding the practice, current and future, of indexical signs subsuming the human sign — of identity becoming indexed as data points rather than human or lived. We talked very briefly about the use of so-called small data in medical practices for diagnostic and health maintenance purposes, along with the use of health product purchasing data by pharmaceutical companies to target advertising toward those who are depressed or under stress, based on their buying habits. He was quite open to the idea of algorithmic rhetoric. And he offered two pieces of advice: talk to the librarians and follow the content. Librarians use algorithms regularly and are well aware of the impact that algorithms have in providing search results. The content I think is about what people are seeking for, although I’m not entirely sure what that means or how it relates. It likely has to do with the materials that pass through our bandwidth, characterizing and beginning to develop algorithmic modeling that can start predicting search results. Maybe. I’ll need to think and read around this topic.

I also met briefly Stephanie Vie and Dawn Armfield, both rhetoric or composition/rhetoric or digital rhetoric and communications scholars that I follow on either Facebook or Twitter. It’s delightful to connect faces to Twitter handles.

I’m already asking myself if I intend to return next year, and I can’t yet answer that. I find the ethos useful and supportive, inviting, even — but I’m not sure that’s going to be enough. I think it will depend on what I believe I can propose in terms of algorithmic rhetoric or technical literacy at the conference, and whether I can find the right group of people with whom to network. Right now games studies, somewhat to my surprise, feels relatively comfortable, even though I myself neither play the games nor think about or theorize their development. But given the way game studies theory addresses agency and rhetorical choices, along with the digital component and the advanced use of technology to code and play games, the intersection of rhetoric and technology appears, at the moment, to include games studies. Perhaps games studies is a boundary object that will enable me to pull together disparate disciplines in a pedagogically sound way that focuses on the technical writing, rhetorical agency, and user-designed interface.

A final note, about being a panel chair. The Myth and Fairy Tales area chair was originally the panel chair for each of the three Myth and Fairy Tale sessions. However, she fell ill and asked each panel if one member would take on the role of chair for the session. I agreed to do so, which explains how I found myself both chairing and presenting in the same panel. I appreciated the opportunity to chair; as a result, I intend to volunteer to chair additional panels in the future, as appropriate and capable, both as valuable experience and as an opportunity to include the experience on my CV.

Southwest Popular/American Culture Association Conference Roundup

I’m returning from the Southwest Popular/American Culture Association (SWPACA) conference in Albuquerque, New Mexico. It’s my first time to this conference, the first time to New Mexico, and the first time to present a paper since my master’s degree days. I’m pleased to report that my paper presentation went well, although I think I excelled more as a panel chair than as a paper presenter. Never mind. I’m fortunate to have skill sets for both.

My paper, Boundary Crossings: (T)here Lies the Trickster, proposed the mythological trickster construct as a contemporary boundary object, synthesizing the boundary object definitions of Star and Griesemer (1989), Popham (2005), and Wilson & Herndl (2007). I used a class I proposed and taught called “Tracking Contemporary Trickster” as a case study demonstrating the benefit that using a trickster lens as boundary object has on the way students see the world.

In a sense this was a remarkably interdisciplinary paper. Although I presented it in one of the Myth and Fairy Tales panels, my topic connected to mythology only in that it used the trickster, a character that appears in many mythologies, as my object of study. My critical approach was application of professional and technical composition theory (the boundary object), while my case study involved pedagogy.

My experience suggests that this interdisciplinarity is the conference’s strength. The conference ethos is deeply accepting and encouraging, and represents, with few exceptions, an invitational rather than persuasive rhetoric. Presentations were not about presenting claims and theories as fact, but were instead aimed at capturing ideas and sharing them with others for consideration and feedback. Post-presentation comments were not about tearing down or critiquing arguments, but about praising areas of strength and offering suggestions for continued, further, or parallel research work. Interdisciplinarity appeared to be encouraged and appreciated, with a range of critical approaches and methods accepted and valued. More importantly, individual presenters were valued, an ethos handed down in large part, as I observed, by the panel chairs.

That said, I didn’t actually find my research niche during the conference. I guess I wasn’t really looking for a niche, but I found several of my ODU colleagues gravitating toward areas of study and consecutive panels in the same areas. Game studies was a very popular strand throughout the conference, and the networking and collegiality of the group was obvious and warm, even inviting to non-games people who were willing to listen and observe. As I seek to further refine my research agenda, particularly in the realm of the intersection of technology and rhetoric, I found the games studies researchers and scholars the most akin to my imagined future work. Digital games are spaces where technology and rhetoric intersect deeply and successfully, as are, perhaps to a lesser extent, classrooms. The parallels between classroom and game are striking and intriguing; there’s a strong case to be made (by Maury Brown or Megan McKittrick and other ODU games scholars, I think) that the classroom itself is game space, or can be conceived of as game space.

A brief chat with Marc Ouellette about indexical signs and algorithmic rhetoric was intriguing. Ouellette shared that he is interested in questions surrounding the practice, current and future, of indexical signs subsuming the human sign — of identity becoming indexed as data points rather than human or lived. We talked very briefly about the use of so-called small data in medical practices for diagnostic and health maintenance purposes, along with the use of health product purchasing data by pharmaceutical companies to target advertising toward those who are depressed or under stress, based on their buying habits. He was quite open to the idea of algorithmic rhetoric. And he offered two pieces of advice: talk to the librarians and follow the content. Librarians use algorithms regularly and are well aware of the impact that algorithms have in providing search results. The content I think is about what people are seeking for, although I’m not entirely sure what that means or how it relates. It likely has to do with the materials that pass through our bandwidth, characterizing and beginning to develop algorithmic modeling that can start predicting search results. Maybe. I’ll need to think and read around this topic.

I also met briefly Stephanie Vie and Dawn Armfield, both rhetoric or composition/rhetoric or digital rhetoric and communications scholars that I follow on either Facebook or Twitter. It’s delightful to connect faces to Twitter handles.

I’m already asking myself if I intend to return next year, and I can’t yet answer that. I find the ethos useful and supportive, inviting, even — but I’m not sure that’s going to be enough. I think it will depend on what I believe I can propose in terms of algorithmic rhetoric or technical literacy at the conference, and whether I can find the right group of people with whom to network. Right now games studies, somewhat to my surprise, feels relatively comfortable, even though I myself neither play the games nor think about or theorize their development. But given the way game studies theory addresses agency and rhetorical choices, along with the digital component and the advanced use of technology to code and play games, the intersection of rhetoric and technology appears, at the moment, to include games studies. Perhaps games studies is a boundary object that will enable me to pull together disparate disciplines in a pedagogically sound way that focuses on the technical writing, rhetorical agency, and user-designed interface.

A final note, about being a panel chair. The Myth and Fairy Tales area chair was originally the panel chair for each of the three Myth and Fairy Tale sessions. However, she fell ill and asked each panel if one member would take on the role of chair for the session. I agreed to do so, which explains how I found myself both chairing and presenting in the same panel. I appreciated the opportunity to chair; as a result, I intend to volunteer to chair additional panels in the future, as appropriate and capable, both as valuable experience and as an opportunity to include the experience on my CV.

Southwest Popular/American Culture Association Conference Roundup

I’m returning from the Southwest Popular/American Culture Association (SWPACA) conference in Albuquerque, New Mexico. It’s my first time to this conference, the first time to New Mexico, and the first time to present a paper since my master’s degree days. I’m pleased to report that my paper presentation went well, although I think I excelled more as a panel chair than as a paper presenter. Never mind. I’m fortunate to have skill sets for both.

My paper, Boundary Crossings: (T)here Lies the Trickster, proposed the mythological trickster construct as a contemporary boundary object, synthesizing the boundary object definitions of Star and Griesemer (1989), Popham (2005), and Wilson & Herndl (2007). I used a class I proposed and taught called “Tracking Contemporary Trickster” as a case study demonstrating the benefit that using a trickster lens as boundary object has on the way students see the world.

In a sense this was a remarkably interdisciplinary paper. Although I presented it in one of the Myth and Fairy Tales panels, my topic connected to mythology only in that it used the trickster, a character that appears in many mythologies, as my object of study. My critical approach was application of professional and technical composition theory (the boundary object), while my case study involved pedagogy.

My experience suggests that this interdisciplinarity is the conference’s strength. The conference ethos is deeply accepting and encouraging, and represents, with few exceptions, an invitational rather than persuasive rhetoric. Presentations were not about presenting claims and theories as fact, but were instead aimed at capturing ideas and sharing them with others for consideration and feedback. Post-presentation comments were not about tearing down or critiquing arguments, but about praising areas of strength and offering suggestions for continued, further, or parallel research work. Interdisciplinarity appeared to be encouraged and appreciated, with a range of critical approaches and methods accepted and valued. More importantly, individual presenters were valued, an ethos handed down in large part, as I observed by the panel chairs.

That said, I didn’t actually find my research niche during the conference. I guess I wasn’t really looking for a niche, but I found several of my ODU colleagues gravitating toward areas of study and consecutive panels in the same areas. Game studies was a very popular strand throughout the conference, and the networking and collegiality of the group was obvious and warm, even inviting to non-games people who were willing to listen and observe. As I seek to further refine my research agenda, particularly in the realm of the intersection of technology and rhetoric, I found the games studies researchers and scholars the most akin to my imagined future work. Digital games are spaces where technology and rhetoric intersect deeply and successfully, as are, perhaps to a lesser extent, classrooms. The parallels between classroom and game are striking and intriguing; there’s potentially a case to be made (one that I think Megan McKittrick is working toward) that the classroom itself is game space, or can be conceived of as game space.

A brief chat with Marc Ouellette about indexical signs and algorithmic rhetoric was intriguing. Ouellette shared that he is interested in questions surrounding the practice, current and future, of indexical signs subsuming the human sign — of identity becoming indexed as data points rather than human or lived. We talked very briefly about the use of so-called small data in medical practices for diagnostic and health maintenance purposes, along with the use of health product purchasing data by pharmaceutical companies to target advertising toward those who are depressed or under stress, based on their buying habits. He was quite open to the idea of algorithmic rhetoric. And he offered two pieces of advice: talk to the librarians and follow the content. Librarians use algorithms regularly and are well aware of the impact that algorithms have in providing search results. The content I think is about what people are seeking for, although I’m not entirely sure what that means or how it relates. It likely has to do with the materials that pass through our bandwidth, characterizing and beginning to develop algorithmic modeling that can start predicting search results. Maybe. I’ll need to think and read around this topic.

I also met briefly Stephanie Vie and Dawn Armfield, both rhetoric or composition/rhetoric or digital rhetoric and communications scholars that I follow on either Facebook or Twitter. It’s delightful to connect faces to Twitter handles.

I’m already asking myself if I intend to return next year, and I can’t yet answer that. I find the ethos useful and supportive, inviting, even — but I’m not sure that’s going to be enough. I think it will depend on what I believe I can propose in terms of algorithmic rhetoric or technical literacy at the conference, and whether I can find the right group of people with whom to network. Right now games studies, somewhat to my surprise, feels relatively comfortable, even though I myself neither play the games nor think about or theorize their development. But given the way game studies theory addresses agency and rhetorical choices, along with the digital component and the advanced use of technology to code and play games, the intersection of rhetoric and technology appears, at the moment, to include games studies. Perhaps games studies is a boundary object that will enable me to pull together disparate disciplines in a pedagogically sound way that focuses on the technical writing, rhetorical agency, and user-designed interface.

A final note, about being a panel chair. The Myth and Fairy Tales area chair was originally the panel chair for each of the three Myth and Fairy Tale sessions. However, she fell ill and asked each panel if one member would take on the role of chair for the session. I agreed to do so, which explains how I found myself both chairing and presenting in the same panel. I appreciated the opportunity to chair; as a result, I intend to volunteer to chair additional panels in the future, as appropriate and capable, both as valuable experience and as an opportunity to include the experience on my CV.

#MakeItHappy and Algorithmic Rhetoric

Check out this Gawker article on its attempts to reveal the insipidity of the nifty algorithm Coca Cola developed as part of its #MakeItHappy Twitter campaign. Several aspects of the story interest me, which I plan to address in upcoming posts. For now, consider this irony: Coke’s algorithm got called out by Gawker’s algorithm.

#MakeItHappy and Algorithmic Rhetoric

Check out this Gawker article on its attempts to reveal the insipidity of the nifty algorithm Coca Cola developed as part of its #MakeItHappy Twitter campaign. Several aspects of the story interest me, which I plan to address in upcoming posts. For now, consider this irony: Coke’s algorithm got called out by Gawker’s algorithm.

Outlining a CV in Composition & Rhetoric

Composition and rhetoric is a little bit of an intimidating field to write one’s CV into, because we study and have expertise on the rhetoricity of things. Applying those same guidelines and standards to my own work can be intimidating. Nevertheless, here’s a beginning outline.

  1. Personal Information
    1. Include meaningful contact information: where I live is useful, but email and mobile phone are probably most meaningful.
    2. Include social media links (but be sure those included and those not included are up to snuff and entirely presentable). The identity we allow others to see who are not our friends is as important to readers of the CV as the identity we create for those who follow or like our social media presences.
    3. Include professional-oriented social media like LinkedIn and Academia.edu. One’s openness and willingness to be identified on social media is part of the rhetorical identity portrayed through the CV.
  2. Education
    1. In reverse chronological order, most current/recent first.
    2. Don’t bother with GPA at this point (I’m 22 years into my professional career). What matters is that I earned degrees from accredited colleges.
    3. Be sure to include thesis and dissertation title, but not abstract.
  3. Publications: Group these in several categories, depending on what’s applicable. I’ll probably go with something like this:
    1. Peer Reviewed
      1. Published
      2. Accepted and Forthcoming
      3. Proposed
    2. Online
      1. Solicited or Responses to Calls
      2. Unsolicited
      3. Guest Posts
    3. Popular
  4. Presentations
    1. Conference
    2. Invited
    3. Informal (not sure what this is going to mean…)
  5. Teaching Experience
    1. Higher Education: Term-by-term summary statement of each class outcome and professional development undertaken as a result, if applicable. [Note: here’s where I wonder if it’s useful to specify anything about student evaluations, because mine are regularly quite strong.]
    2. Secondary: Quick listing of classes
    3. Noncredit or Others: Include guest lectures, church teaching experiences, other non-traditional instructional opportunities. <– This is probably a way to demonstrate a career-long dedication to pedagogy, perhaps a differentiator when applying to a school with strong instructional requirements.
  6. Service: I think I’ll present this as pedagogical and community. As a composition teacher, my work is often in service to all other disciplines; as a professional and as a person, I give back to my professional, personal, and religious communities and want it known that I do so.
    1. Pedagogical (Just a mention that I teach composition)
    2. Professional
    3. Personal
  7. Grants: I have little to show here, but I don’t see much benefit of grouping these with granularity.
  8. Professional: This is an area unique to my experience: I have LOADS of professional experience in higher education and nonprofits that is not “academic” or “scholarly.” As a result, I want to be able to highlight my work history in several categories.
    1. Web Development
    2. IT Management
    3. Educational Leadership
  9. Professional Development
    1. Webinars
    2. Conferences
    3. Classes
  10. Honors and Awards
    1. Offices held/Appointments received
    2. Awards and honors received (I think I’ll go back to undergraduate, but probably don’t need to. Only if appropriate to Comp/Rhet experience.)
    3. Other ways of being honored (honorary degrees, employee of the month, etc.)
  11. Interests: A way to reach beyond the scholarly and point to areas of intersection between personal, professional, community, and service. In my case, my interests are in technologies, especially new technologies.
  12. References

Outlines: CC-licensed Flickr image courtesy mkorsakov

Outlining a CV in Composition & Rhetoric

Composition and rhetoric is a little bit of an intimidating field to write one’s CV into, because we study and have expertise on the rhetoricity of things. Applying those same guidelines and standards to my own work can be intimidating. Nevertheless, here’s a beginning outline.

  1. Personal Information
    1. Include meaningful contact information: where I live is useful, but email and mobile phone are probably most meaningful.
    2. Include social media links (but be sure those included and those not included are up to snuff and entirely presentable). The identity we allow others to see who are not our friends is as important to readers of the CV as the identity we create for those who follow or like our social media presences.
    3. Include professional-oriented social media like LinkedIn and Academia.edu. One’s openness and willingness to be identified on social media is part of the rhetorical identity portrayed through the CV.
  2. Education
    1. In reverse chronological order, most current/recent first.
    2. Don’t bother with GPA at this point (I’m 22 years into my professional career). What matters is that I earned degrees from accredited colleges.
    3. Be sure to include thesis and dissertation title, but not abstract.
  3. Publications: Group these in several categories, depending on what’s applicable. I’ll probably go with something like this:
    1. Peer Reviewed
      1. Published
      2. Accepted and Forthcoming
      3. Proposed
    2. Online
      1. Solicited or Responses to Calls
      2. Unsolicited
      3. Guest Posts
    3. Popular
  4. Presentations
    1. Conference
    2. Invited
    3. Informal (not sure what this is going to mean…)
  5. Teaching Experience
    1. Higher Education: Term-by-term summary statement of each class outcome and professional development undertaken as a result, if applicable. [Note: here’s where I wonder if it’s useful to specify anything about student evaluations, because mine are regularly quite strong.]
    2. Secondary: Quick listing of classes
    3. Noncredit or Others: Include guest lectures, church teaching experiences, other non-traditional instructional opportunities. <– This is probably a way to demonstrate a career-long dedication to pedagogy, perhaps a differentiator when applying to a school with strong instructional requirements.
  6. Service: I think I’ll present this as pedagogical and community. As a composition teacher, my work is often in service to all other disciplines; as a professional and as a person, I give back to my professional, personal, and religious communities and want it known that I do so.
    1. Pedagogical (Just a mention that I teach composition)
    2. Professional
    3. Personal
  7. Grants: I have little to show here, but I don’t see much benefit of grouping these with granularity.
  8. Professional: This is an area unique to my experience: I have LOADS of professional experience in higher education and nonprofits that is not “academic” or “scholarly.” As a result, I want to be able to highlight my work history in several categories.
    1. Web Development
    2. IT Management
    3. Educational Leadership
  9. Professional Development
    1. Webinars
    2. Conferences
    3. Classes
  10. Honors and Awards
    1. Offices held/Appointments received
    2. Awards and honors received (I think I’ll go back to undergraduate, but probably don’t need to. Only if appropriate to Comp/Rhet experience.)
    3. Other ways of being honored (honorary degrees, employee of the month, etc.)
  11. Interests: A way to reach beyond the scholarly and point to areas of intersection between personal, professional, community, and service. In my case, my interests are in technologies, especially new technologies.
  12. References

Outlines: CC-licensed Flickr image courtesy mkorsakov

Samuel’s Words Never Fell to the Ground

“The LORD was with Samuel as he grew up, and he let none of Samuel’s words fall to the ground.” I Samuel 3:19

I teach Sunday School at a Baptist church. Let me be a little more accurate: I alternate discussing Biblical principles with high school seniors and young adults ages 18-22 or so. These classroom sessions occur on Sunday mornings.

I don’t do much “teaching” in the sense of lecturing on Biblical truths or some kind of exegetical analysis of scripture. I  facilitate discussions on ways to apply the words from scripture in our daily lives, within the lived experience of the students in the class. I spend my time preparing to ask question that will encourage students to think about their own faiths and propose ways of reacting to scriptures. And we spend most of our time building community and building each other up, because that’s how I think about applying my understanding of scripture to myself and others.

This morning I brought up the story of Samuel to illustrate the concept of vocation, or calling. We talked about callings, about their origins and results, about how we know we’ve received a call. One of the interesting points made was that callings are about relationships: in order to be called, someone must be doing the calling. That places our vocations within the embrace of our relationship with the one calling us. We talked about God’s calling, and we also discussed whether others can call us. We didn’t answer most of our questions; my goal as a teacher is never to try to answer the questions, but to create a community in which the questions can be raised and explored in a safe and encouraging environment.

This post, however, is not about the class. It’s about a verse I encountered, the one written at the top of the post. What caught my attention was the phrase “and he let none of Samuel’s words fall to the ground.” I figured there must be something strange in the translation, so I looked up the original Hebrew. Here’s what it says:

וַיִּגְדַּ֖ל שְׁמוּאֵ֑ל וַֽיהוָה֙ הָיָ֣ה עִמֹּ֔ו וְלֹֽא־הִפִּ֥יל מִכָּל־דְּבָרָ֖יו אָֽרְצָה׃

For those who don’t read Hebrew, I’ll transliterate to the best of my ability. I’m not a Hebrew scholar; I’m a once almost-fluent Hebrew speaker who learned the modern language while living in Israel.

“And Samuel grew and Adonai was with him and never have fallen [any] from all his sayings to the ground.”

God kept Samuel’s sayings — not just his words, but his communications, the things he said — from falling to the ground.

As a student of rhetoric and composition, this is a remarkable idea. That God can be engaged in protecting one’s sayings, one’s communications, is a remarkable thing. I assume this phrase is idiomatic in ancient Hebrew; I’ve not done the research, but I think I will. Or if you know, post a comment and let me know.

But here’s what I took away from the verse: it’s possible for one’s communication, one’s sayings, to be protected from destruction or being ignored.

I would like very much if one could say about my own sayings that they never fell to the ground. That would be a remarkable legacy.

Case Study #4: FrankenTheory

Boundaries in My Analysis of Google Analytics

I am limiting my analysis of Google Analytics as an object of study by focusing on its activities and its data model as reported in terms of dimensions and metrics.

  • Google defines Analytics activity as collection, collation, processing, and reporting.
  • Google describes its data model as consisting of user, session, and interaction.
  • Google collects and reports data in terms of dimensions (“descriptive attribute or characteristic of an object”) and metrics (“Individual elements of a dimension that can be measured as a sum or ratio”) (Google, 2014).

These limits and terms are described in detail in my earlier Re/Proposed Object of Study: Google Analytics blog post.

I chose GA as my object of study because it’s a tool with which I work on a daily basis. I proposed GA as my object of study to my boss, the director of our school’s marketing and communications team, before formally proposing it in class because I wanted approval to use our school’s GA account in my study. I also expected my study to contribute to my understanding and use of GA in web development and management. A deeper understanding of GA as a network has provided both a tool for theoretical exploration and practical application.

Here’s an example of how applied this theoretical study has become. On April 16, with little fanfare, Google announced that it was replacing the term “visit” with the term “session” in its reports. I missed the announcement entirely, so I was surprised while measuring the result of online advertising efforts in our campus newspapers to discover that the “unique visits” metric that I had been using was no longer available; instead, it had been replaced by the “sessions” metric, without the “unique” modifier. I was also surprised to discover that the “unique visits” metric I had been using did not match the “sessions” metric when I re-ran prior reports to test data accuracy reports; “sessions” reported higher numbers than “unique visits” had reported. As we reached the first of May, when I normally complete April reports, I realized the full extent of the terminology change: “unique visits” were no longer being measured. Two plus years of reporting data were potentially compromised as inaccurate, since we report data for month on month and year on year comparisons (e.g. does April 2014 look better than April 2013 in terms of overall unique web visits, and does the calendar year-to-date period of January-April 2014 look better than the previous January-April 2013 period?).

As a result of my study of the structure and function of Google Analytics, I had learned how GA counts session data. Critical inquiries had questioned whether GA’s reporting of unique visits could be accurate given the browsing patterns of today’s web visitors. Visits (now sessions) are defined as individual browsing sessions on a given website on a given browser and platform. A visitor (now user) who visits the same website using two different browsers (Chrome and Firefox, for instance) would be calculated as two unique visits (when unique visits were provided) because the session is browser specific. Furthermore, a visitor who visits the same website on a desktop platform browser, then revisits the same website on a mobile device, would be calculated as two unique visits, because the session is platform specific. In short, “unique visit” is really a calculation of “individual session” without a distinction of uniqueness of the visitor. Using the term “unique visit” suggested (and my marketing team and I took it to mean) visits by unique users, a measurement we considered superior because it suggested the actual number of visitors. What we should have been measuring, however, was visits, regardless of their “uniqueness,” because there was no unique quality to the visit in terms of the visitor. The end result is that I will need to re-record our historical data in terms of sessions rather than unique visits, potentially revealing visit patterns we had not before seen or understood.

Without this study of GA as a network, I would not have understood why reporting data did not match, and I would have struggled to find documentation of the issue. There remains little documentation from Google itself about the disappearance of unique visit as a reported metric as of this date. In short, the application of my theoretical exploration directly benefited my and my team, and ultimately our school and our understanding of our data within the framework of industry benchmarks.

Theories of Networks and Google Analytics

I’m using two theories — Castells’ network society and Deleuze & Guattari’s rhizome — to flesh out my understanding of Google Analytics and sketch out my Frankentheory of a network.

First, here’s a review of some familiar territory: My application of Castells’ network society to GA from Case Study #2. I’ve brought this in as a piece rather than linking to it because I’d like to make departures from specific aspects of this application in discussing Deleuze & Guattari and in sketching out a Frankentheory.

Defining Google Analytics

Castells (2010) considers technology to be society (p. 5). As a result, GA can be considered social. As an information technology, GA creates active connections between websites (data collection), Google data centers (data configuring and processing) including aggregated tables (processing), and GA administrator accounts (configuring and reporting). These active connections collect, mediate (configure and process), and report on the three aspects of the GA data model consisting of users, sessions, and interactions. These connections represent social actions. So Castells (2010) might define GA as a global informational network (p. 77) that collects data from and reports data to local nodes (websites). Google servers where data are configured and processed might be considered mega-nodes (xxxviii) that, through the iterative process of increasing user visits and interaction by improving website design and content based on GA reported results, impose global logic on the local (xxxix).

Nodes in Google Analytics

Screen Shot 2014-04-12 at 9.33.26 PM

Google Data Center Locations: Image from Google Data Centers.

Individual websites, GA account administrators, and website visitors are local nodes in the global informational network. Google data center servers are mega-nodes in the network. Google employees who program GA and maintain Google servers and centers are localized nodes in the global network. Google’s data centers are located in a variety of locations that include North America, South America, Europe, and Asia. Several are found in Castells’ (2010) “milieux of innovation” (p. 419) including Taiwan, Singapore, and Chile. Others are found in what appear to be unlikely global spaces, including Council Bluffs, Iowa, and Mayes County, Oklahoma. These locations reiterate Castells’ insistence that local and global are not mutually exclusive polar opposites; rather, the new industrial system is neither global or local, but a new way of constructing local and global dynamics (p. 423). Websites, administrators, visitors, servers, and employees are simultaneously localized nodes (even the the mega-nodes are situated in space and time) in the global informational network.

Agency among Google Analytics Nodes

GA account administrators and website visitors have the greatest level of agency in the network, while Google employees exert limited agency within the confines of their labor relationships and conditions. Account administrators would likely be considered among Castells’ (2010) “managerial elites” (p. 445), while Google employees who maintain and program the servers might be part of Castells’ disposable labor force (p. 295). Account administrators have the authority to configure GA data, including the ability to filter out results, narrow data collection according to metrics and dimensions, and even integrate external digital metrics in GA. This authority is not, of course, the authority of Google’s corporate structure and hierarchy, but within the boundaries of GA data model and activities, account administrators exude authority. Website visitors may choose to visit, or not visit, any given website, once or more than once (meaning a single session or multiple sessions). This agency includes the power to intentionally separate themselves from the network, meaning that, for users, they only enter into the network as a node when they visit the tracked website. Interestingly, only the GA administrator has authority to eliminate users from the network; account configurations may filter out visitors along several dimensions.

Nodal Situation and Relation

Nodes are locally situated. While simultaneously part of the global informational economy, all of the nodes in the GA network are situated in a space and time. This simultaneous here/there compression of space and time is the origin of Castells’ (2010) “space of flows” (p. 408) and “timeless time” (p. 460). Websites are simultaneously hosted on physical servers around the world and locally viewed on specific platforms and media. Users are simultaneously accessing global data in territorial space on hardware. GA administrators are situated while configuring accounts and loading reports from the cloud. Google data centers are situated in specific locations, but they collect and process global data from local spaces and times. Google employees are culturally and territorially situated in the global Google labor pool.

Data rarely travels along parallel paths in the GA data model or GA activities. Website visit data are collected in the data modeluser, session, and interaction data — and sent to Google data centers for processing and configuration. Other than writing unique user identification data onto cookies on users’ browsers or apps, little data travels from GA to users. Website content is indirectly affected by GA reports configured and read by GA administrators, but within the GA activity network, websites are unaffected by GA activity on the data model. Beyond the boundaries of the OoS, of course, Google serves plenty of data, in the form of ads, back to users. But that’s now beyond the scope of this study.

Movement in the Network

Framework for Movement: Wires in The Dalles, Oregon, Google Data Center. Photo from the Google Data Center Gallery.

Data moves in GA. More specifically, data in the GA data model moves in GA. Data are initiated by users visiting tracked websites. Specific frameworks must be in place for connections to occur and data in the data model to be collected. Namely, websites must contain GA tracking code, embedded in the website code through the agency of the GA administrator. The embedded GA tracking code enables, and the web browser and hardware afford (Norman, n.d.), the user to initiate a tracking pixel (gif) and generate data to be collected in the GA data model. Once collected, the data are configured (by the account administrator and by the GA algorithms), processed (in a largely opaque manner) and collated in aggregated data tables, and reported in visual and tabular representations. In Castells’ (2010) terms, data represent flow in the GA network (p. 442). That data is both spatial and temporal (it comes from and is attached to a specific territory and represents a specific, chronological activity), but it is also entirely global and digital.

Content in the Network

Data are collected and packaged — literally, in a gif image pixel — in parameters relating to user, session, and interaction. The GA tracking code encodes data and sends it to Google data centers where the data are decoded, configured based on administrator preferences, processed and repackaged in aggregated data tables, and made available to the account administrators. The reporting function remediates the data in visual and tabular formats for ease of reading and use. While the data reported are considered authoritative and authentic, the actual processing function remains largely proprietary, with only end results available to extrapolate what processing actually occurs. This black boxed processing function seems unlikely to represent Latour’s (2005) intermediary; as Fomitchev (2010) claims, there are probably processing functions that result in highly mediated, possibly even inaccurate, results. Castells (2010) would likely measure GA performance based on “its connectedness, that is, its structural ability to facilitate noise-free communication between its components” (p. 187). I hope we will see increased academic scrutiny focused on this perceived intermediary function in GA, even as we scholars rely on its results.

Birth and Death of a Network

Killing the Network: Failed Google data hard drives to be destroyed at the St. Ghislain, Belgium, Google Data Center. Photo from the Google Data Center Gallery.

Castells (2010) indicates that global informational networks emerge within milieux of innovation. These main centers of innovation are generally the largest metropolitan areas of the industrial age (p. 66), able to “generate synergy on the basis of knowledge and information, directly related to industrial production and commercial applications” (p. 67), and combine the efforts of the state and entrepreneurs (p. 69). Nodes on the network get ignored (and therefore cease to be part of the network) when they are perceived, by either the network or by its managerial elites, to have little value to the network itself (p. 134). The GA network grows as more nodes are added, either as users or as web pages with tracking code. GA administrators have agency to kill network nodes by removing tracking code from pages, or by directing IT managers to remove poorly performing web pages. Users have agency to quit visiting a website, thereby removing its value to the person. While many other actions by agents outside the GA network may affect the growth or dissolution of the network, they are outside the boundaries of the GA activity and data model.

And Now, the Rhizome

First a note about using Deleuze & Guattari. I did not enjoy or particularly “get” this reading the first time around. I grasped the broad strokes of the argument, but this is a chapter that requires close, multiple readings. What I discovered as I re-read the chapter in light of this analysis was that it addresses a significant aspect of networks that Castells does not — namely, a rhizomatic approach to networks problematizes the very definition of GA I established during my Re/Proposal. In short, applying Castells profited from the boundaries I placed on the OoS; applying Deleuze & Guattari requires eliminating the boundaries, preferring instead a situated, chronological cross-section as a set of boundaries enabling analysis.

Second, a note about this cross-sectional approach. In my scaffolding outline, I referred to a “flattened, rhizomatic” approach to composing and networks. Placing these two concepts together elicited useful feedback and discussion during the following class, as a result of which I realized that rhizomes are not naturally flattened. While Deleuze & Guattari (1980/1987) refer to flattened multiplicities, they do so in the context of many dimensions: “All multiplicities are flat, in the sense that they fill or occupy all of their dimensions” (p. 9). In fact, rhizomes are unpredictably dimensional; connections can and must occur along all dimensions: “any point of a rhizome can be connected to anything other, and must be” (p. 7). Since the boundaries of such a “network” can’t really be established, one way to analyze the rhizome is to take a cross-sectional slice, situated in space and time, of the rhizome and examine the relationships among points in the rhizome in this “flattened” slice. The rhizome is a multidimensional assemblage, not a flattened network.

These two notes represent realizations that complicate and problematize the restrictive perspective I offered of GA as a network. Limiting the network to GA activities and data model resulted in limits to what I could discuss in my application of Castells. For example, in discussing the birth and death of the network, I cut short my analysis with this limiter: “While many other actions by agents outside the GA network may affect the growth or dissolution of the network, they are outside the boundaries of the GA activity and data model.” Similarly, when addressing nodal situation and relations, I wrote this limiting statement: “Beyond the boundaries of the OoS, of course, Google serves plenty of data, in the form of ads, back to users. But that’s now beyond the scope of this study.” These limits were real — the boundaries I established for describing GA as a network did, in fact, prevent addressing aspects of the network — but they do not reflect an accurate mapping of GA network activity. Deleuze & Guattari (1980/1987) point out that “the rhizome is altogether different, a map and not a tracing” (p. 12, emphasis original). Tracing is the role of centralized control, of perspectives limited by binaries and “tree logic”: “What distinguishes the map from the tracing is that it is entirely oriented toward an experimentation in contact with the real” (p. 12). A mapped understanding of GA must address its real complexity, its nodes and connections in terms of real experiences, not centrally-defined boundaries.

A mapped, cross-sectional perspective on GA as a network was, to my surprise, the goal of my first case study. In fact, the first visualization of the network I provided was a portion of a Popplet titled “Visualizing a Partial Google Analytics Data Set.”

Screen Shot 2014-05-06 at 8.03.11 PM

Figure 1: Visualizing a sample Google Analytics data set from Case Study #1Popplet

My original attempt to visualize and define GA as a network was more chaotically rhizomatic than any other depiction I’ve attempted since. In fact, for much of the rest of the semester, I’ve been struggling to trace my understanding of GA as a network, when in fact Deleuze & Guattari would have me do precisely the opposite: map the multiplicity of GA as assemblage, depicted as a cross-sectional portion of the network situated in time and space.

Mapping GA as rhizome means accepting that users, servers, computers, mobile devices, browsers, operating systems, marketers, developers, programmers, designers, GA account administrators, Google data centers, Google programmers and server maintenance personnel, homes, home offices, office buildings, network cables, routers, switches, weather conditions, satellites, trans-Atlantic communications cables, seawater, signal degradation, electrons, light energy, insulators, and theorists must be included as nodes in the GA rhizome. GA collects data on some of these dimensions; other dimensions, however, are embedded as affordances and constraints to the web technologies that enable GA to measure dimensions at all, so these affordances and constraints must also be depicted in a cross-section of GA as rhizome.

There’s a reason Deleuze & Guattari did not include a visualization of the rhizome on their chapter. It’s too complex, too multi-dimensional, to capture in a 2-dimension drawing. But I’m going to give it a shot.

Popplet mind map

Figure 2: Visualizing Google Analytics as a Rhizome—Popplet

Figure 2 depicts a rhizome cross-section of a single node, User, and the connections that exist among dimensions of the GA data model, website affordances and constraints, website creators, and Google personnel. What this depicts is that a User connects from and to most of the nodes, that the nodes connected to the User are connected to one another, and that relationships proliferate exponentially if extrapolated to the entire list of dimensions. And these dimensions are themselves necessarily limited (perhaps even cross-sectioned) by the visualization technology and my own time and patience. Were I to connect all of the non-technological aspects to the User—like location and weather conditions — the rhizome could go on forever. The point is that mapping the actual rhizome, rather than tracing the limits of the network, generates the rhizome itself. Or, as Deleuze & Guattari (1980/1987) propose, “The map does not reproduce an unconscious closed in upon itself; it constructs the unconscious. It fosters connections between fields, the removal of blockages on bodies without organs, the maximum opening of bodies without organs onto a place of consistency. It is itself a part of the rhizome” (p. 12).

Closing Gaps

Castells offers a remarkably cogent and highly matched means of analyzing GA as a network as defined by Google itself: in terms of GA activities and the GA data model. Castells addresses issues of localization and globalization in ways that make sense for GA defined as Google defines it. Here’s my conclusion from Case Study #2.

While Castells addresses the local, he tends to discuss localization in terms of groups rather than individuals. In this way, Castells more closely resembles ecological theories that apply to organism categories rather than to individual organisms. He regularly refers to groups of people and nodes: the managerial elites (rather than individual leaders), the technological revolution (rather than revolutionary technology pioneers), and the global and local economy (rather than the economic wellbeing of the individual small business owner). The result is that I can’t really address the individual user as a single agent in GA. Then again, this is hardly a hardship, in that GA aggregates data and anonymizes identities. GA, too, resembles an ecological theory rather than a rhetorical theory; it focuses on profiles of territorially localized users rather than individual users in a specific city. As a result, Castells and GA match rather nicely in defining the boundaries of the discussion. In fact, I’d argue that GA (and Google more broadly) represent precisely the network society Castells defined in his text. It’s interesting that he didn’t predict or recognize the rise of Google as I would have expected him to do in his 2010 preface. And Castells’ (2010) discussion of communication media clearly did not predict the popularity or ubiquity of Google’s YouTube on the network as a differentiated medium whose content is driven by user tastes and users-as-producers (p. 399).

Once we admit the possibility that GA is not just what Google says it is, but that GA represents a much wider and broader rhizome of connections, Castells no longer adequately describes the network. GA as rhizome requires additional theoretical application for understanding and visualizing.

Frankentheory

After a semester of theorizing, what’s my own theory of networks?

Rhizome illustration

What I think a rhizome looks like. “The Opte Project” by Barrett Lyon. Creative Commons licence CC BY-NC-SA. From The Accidental Technologist‘s post The Way of the Rhizome #h817open

Networks are local. They are also global. This is not dualism, but convergence. Local and global converge in time and space, and we must be prepared to engage in both simultaneously. The global remains rooted in the local; local conditions and environments affect and influence connections to the global. In our efforts to understand global network activity, we should not lose sight of the affordances and constraints of local conditions, including available access to the internet, proximity to other nodes, and the politics of nodal connectivity.

Networks enable nodes. A collection of nodes does not a network make. Networks enable nodal activity; this means that network frameworks must be in place for networks to exist and start collecting nods. This also means that the activity of collecting nodes in networked. The network can grow well beyond its framework in unexpected and unpredictable ways, and this should be expected, anticipated, and planned to the extent possible.

Networks are rhizomes. Or at least rhizomatic. They are unlikely to require or have inherent hierarchical structures; these will have to be applied to the network. Rhizomatic structure and growth suggest unpredictability of nodal connections. As I understand rhizomes, the importance of any node being able to connect to any other node — or to anything, for that matter — cannot be overstated. It is this aspect of rhizomatic connectivity that I would consider “flat.” There are neither more nor less important nodes; there are no inherent political relationships between and among nodes. Any political power attributed to the node will either be self-contained or bestowed from outside the rhizome; within the ecology of the rhizome, all nodes are equally capable of connecting to all other nodes and to anything outside the rhizome. In this sense, I would suggest that rhizomes are politically flat.

Networks can be analyzed in cross-section; they are very difficult to analyze in real time as they exist. They are both too large to examine as a whole and too complex to analyze as active connections are “firing.” Cross-sections can be taken of specific aspects of the network or of the network as a whole. Cross-sections are frozen in time and show little activity, merely traces that can be followed and explored. Networks contains a multiplicity of simultaneous connective activity; our abilities to analyze simultaneity is limited. Instead, we must follow specific threads of connectivity through time and space to analyze them. Such analysis is made possible through cross section.

Google Analytics’ Contributions to English Studies

First, GA can and should be critically examined as a rhetorical technology. GA activity includes reporting. These reports are discursive and rely on visual and written rhetoric to communicate meaning. The “meaning” of a GA report can be manipulated like any other statistical data. Its meanings depend on local environment and conditions, comfort with standard and local meanings of GA terminology (like “session” or “user,” for example), and familiarity with the GA data collection model. Its visualizations can be analyzed for clarity and transparency, for cultural or sociological bias (related to colors used, default views, and other determined factors), and for its connectedness to other discursive elements (like websites whose visitor traffic it measures). Critical rhetorical analysis of GA reports could easily be an object of study by itself.

Second, GA can and should be critically approached as a black-boxed network whose data manipulation and configuration are largely hidden, lacking transparency. Google’s business model depends on its proprietary search results algorithms. It protects that algorithm carefully; while GA reporting is not directly dependent on the search algorithm, website visit data contribute to search results. Full disclosure of its data configuration and processing activities would likely reveal much about Google’s search algorithm; as a result, these processes are only partially disclosed. Google’s own Analytics help files and tutorials explain the order, purpose, and general procedures of data configuration and processing, but these files and tutorials do not reveal in-depth specifics on how collected data are processed into aggregate tables, nor how those tables are then indexed for rapid, near-instant on-the-fly reporting. Google’s market share in web search and advertising result in the formation of what Althusser (1971) called a repressive state apparatus; I suggest that GA is an ideological expression of that apparatus, or an ideological state apparatus. While neither Google nor GA is a state in a political sense, its size and clout suggest an industrial state-like entity with resources and influence strong enough to manipulate or evoke responses from other political entities, as it has done recently in relations with the government of Russia (Khrennikov & Ustinova, 2014).

Third, GA results themselves can and should be critically examined. Far too many otherwise critically-written journal articles use GA results as instrumental rather than mediated. That is, GA report data are accepted as unqualified and accurate reflections of website traffic rather than mediated reports of visitor activity. Little care is given to providing GA-specific definitions of terminology like “session” and “user.” This acceptance can result in significant reporting issues — I’m experiencing a particular situation as I type in which Google has revised a reporting criterion from “visits” to “sessions.” While these two terms are being used synonymously, one implication is that GA has removed the dimension of “unique visit” from its reporting matrix. GA’s definition of session doesn’t differentiate between unique or repeat visits among sessions, as each session is considered a unique event regardless of the identity (which may not be accurately known) of the visitor. Several reports I provide my dean and marketing director were based on unique visit numbers; as a result, I’m forced to rework all of my reports to reflect sessions rather than unique visits. This has implications for perceptions of “progress” and “improvement” among senior leadership, a particularly uncomfortable reality brought to bear this week. (Google changed its reporting structure without fanfare on April 16, announced in a Google+ post.)

Finally, GA’s data collection method can and should be understood as discursive. Individual GIF calls that report data back to Google servers do so in text tags attached to tracking pixels generated through data collection. For example, every GA tag begins with “utm,” a prefix whose meaning is unclear. Many data points are collected in abbreviations whose symbolic meanings would be interesting to explore. Again, GA offers few clues for more obscure abbreviations, although Google does provide a list of many (but not all) dimensions collected via tracking pixel calls. Some of these symbols are explained in the Google Developers (2014) Tracking Code Overview. While parameter abbreviations are obscure, the values themselves are even less clear. Consider the parameter/value pair “utmul=pt-br”: the utmul parameter represents “browser language” while the pt-br value represents “Brazilian Portuguese.” This symbolic communication system is itself fodder for rhetorical analysis and interpretation.

References

Althusser, L. (1971). Ideology and ideological state apparatuses (Notes towards an investigation). In B. Brewster (transl.) & A. Blunden (trans.), Louis Althusser archive. Retrieved from https://www.marxists.org/reference/archive/althusser/1970/ideology.htm (Original work published in Lenin philosophy and other essays)

Castells, M. (2010). The rise of the network society [2nd edition with a new preface]. Chichester, UK: Wiley-Blackwell.

Deleuze, G., & Guattari, F. (1987). A thousand plateaus: Capitalism and schizophrenia. (B. Massumi, Trans.) Minneapolis, MN: University of Minnesota Press. (Original work published 1980)

Google. (n.d.). Algorithms. Inside Search. Retrieved from 1 May 2014 from https://www.google.com/insidesearch/howsearchworks/algorithms.html

Google. (2014). Dimensions and metrics. Google Analytics Help. Retrieved from https://support.google.com/analytics/answer/1033861?hl=en

Google Analytics. (2014, April 16). Understanding user behavior in a multi-device world (Web post). Google+. Retrieved 1 May 2014 from https://plus.google.com/+GoogleAnalytics/posts/LCLgkyCn4Zi

Google Developers. (2014, April 16). Tracking code overview. Google Developers. Retrieved from https://developers.google.com/analytics/resources/concepts/gaConceptsTrackingOverview#gifParameters

Krennikov, I., & Ustinova, A. (2014, May 1). Putin’s next invasion? The Russian web. Bloomberg Businessweek. Retrieved from http://www.businessweek.com/articles/2014-05-01/russia-moves-toward-china-style-internet-censorship

[ Feature image: Today's latte, Google Analytics. CC licensed image from Flickr user Yuko Honda ]

Coda: Rickert’s Wonderful World of Oz Meets Pocahontas

First, an aside: I couldn’t stop myself from thinking of this scene from The Wizard of Oz in an entirely new way. While it’s clearly made with the human worldview of home in mind, I began to think of the … Continue reading

Mindmap #13: Concept Groupings 1

This week is the first of two focused on grouping theorists and/or theories by concepts. I identified five concept groups to which I’ve connected theories: Agency, Flow, Meaning, Boundaries, and Composition/Rhetoric. I’ve included a screenshot of the area I’ve set aside for concept grouping, along with a full-map version.

Popplet mindmap visualization

Concept Groupings, Week 1 (Inset): Putting Theories in Place (Popplet)

Popplet mindmap visualization

The Entire Mindmap: Concept Groupings on the Left (Popplet)

I described the concept groups as follows:

  • Agency: Individual nodes (as opposed to groups of nodes) are given partial or full agency in the network.
  • Flow: There is movement of some material through or in the network.
  • Meaning: That which flows through the network has intrinsic meaning; it is not simply material.
  • Boundaries: The theory offers some recognition of boundaries of the network, either as affordances or as constraints to the operation or definition of the network.
  • Composition/Rhetoric: Theory offers direct or indirect reference to rhet/comp, or originates in rhet/comp.

I chose these concepts in part because several have been part of our inquiry throughout the semester and in part because these are aspects of networks that interest me most. I am becoming especially interested in boundaries in networks, whether the result of framework or infrastructure constraints or the result of relatively arbitrary efforts to circumscribe networks for study or description.

Geopolitical boundaries fascinate me, the result of growing up in Israel. I experienced early in my adolescence the arbitrary nature and origin of current Middle Eastern boundaries initiated through global political interests and will after World War I and, to a lesser extent, World War II. With an Israeli visa stamp in my passport, I remain a victim of those arbitrary borders — with few exceptions, I can’t cross the border into most Arab states using that passport. I can visit Egypt, Jordan, Morocco, Oman, and UAE, but I’m unable to visit Syria, Lebanon, Iran, Iraq, Saudi Arabia, smaller Persian Gulf states or North African Arab states (Israeli Passport, 2014).

I would argue that the root of many socio-political conflicts in the Middle East stem from global influence on local boundaries. For example, the current Syrian civil war pits the minority Alawite ruling authority against the Sunni majority, the result of poorly-planned and articulated boundaries among various people groups with historic enmity toward one another. Not that individual nation-states or regions for specific people groups is the answer — reference ongoing enmity between Pakistan and India — but borders drawn in collaboration with, rather than enforced upon, local groups would surely have addressed, even mitigated, some of the pent-up enmity that has recently exploded in violence in Syria and surrounding nations. Boundaries are deeply decisive in the Middle East as borders, but they are also deeply decisive as concepts and socio-political realities. The result of divisiveness (differentiation) is discourse, and the rhetoric of boundaries, whether in reference to tricksters or Middle Eastern borders or networks, fascinates me.

At any rate, this week I limited connections to the theories rather than the theorists. I’ve maintained a running list of theories in the upper-left corner of my mindmap, each of which I’ve connected as Theorized and/or Operationalized. I’ve used that list of theories for connections. Next week, in addition to adding a concept or two, I’ll connect individual theorists to the concept groupings. This will weave a remarkably tangled web. It might even be ambient.

Reference

Israeli passport. (2014, March 27). Wikipedia. Retrieved 19 April 2014 from http://en.wikipedia.org/wiki/Israeli_passport

[ Feature image: The wall between Israel and Palestine. CC licensed image from Flickr user Peter Barwick ]