Link – MP3 Download

I’m looking forward to continuing this research in the spring – we’re currently scheduling a seminar at UNC’s Institute on Aging, so I will share the date of that seminar when we get that on the books.

Link to the show (direct MP3 download)

The segment on Freedom is about 30 minutes in.  I enjoyed hearing Peggy talk about her work on the article, and her use of Freedom.

Not long ago, I started an experiment in self-binding: intentionally creating an obstacle to behavior I was helpless to control, much the way Ulysses lashed himself to his ship’s mast to avoid succumbing to the Sirens’ song.

And that is why I need the mast. It came in the form of an app called Freedom, which blocks your Internet access for up to eight hours at a stretch. The only way to get back online is to reboot your computer, which — though not as foolproof as, say, removing the modem entirely and overnighting it to yourself (another strategy I’ve contemplated) — is cumbersome and humiliating enough to be an effective deterrent. The program was developed by Fred Stutzman, a graduate student in information and library science, whose own failsafe self-binding technique — writing at a cafe without Internet access — came undone when the place went wireless. “We’re moving toward this era where we’ll never be able to escape from the cloud,” he told me. “I realized the only way to fight back was at an individual, personal level.”

Orenstein goes on to write:

It could be that sometimes our greatest freedom may be to choose freedom from freedom. I am still surprised by the relief that floods me whenever I bind myself from going online, when I have no option but to ignore the incessant tweets and e-mail messages and videos and news links and even the legitimate research.

I’m not wishing the Internet away. It has become so integral to my work — to my life — that I honestly can’t recall what I did without it. But it has allowed us to reflexively indulge every passing interest, to expect answers to every fleeting question, to believe that if we search long enough, surf a little further, we can hit the dry land of knowing “everything that happens” and that such knowledge is both possible and desirable. In the end, though, there is just more sea, and as alluring as we can find the perpetual pursuit of little thoughts, the net result may only be to prevent us from forming the big ones.

First things first, it is a tremendous honor (an a little surreal) to be featured prominently in the New York Times Magazine.  My goal in designing software is to solve complex problems through simple design, and it is heartening to know that I’ve helped people become more productive and accomplish their goals.

The point Orenstein makes is that our inundation with little-k knowledge – extensively afforded by the Internet – stands in the way of production big-K knowledge – our books, dissertations, and large-scale projects.  By stepping away and freeing one’s self from the stream – by finding freedom in Freedom – we are able to focus anew on Knowledge.

The privileging of Knowledge over knowledge is essentially a value-enforcing process (see Foucault’s lecture Truth and Power or the long-form Archaeology of Knowledge), one that is troubling as we privilege certain forms of literacy and marginalize others (e.g. Wikipedia, digital literacies, etc).  But there remains a simple fact that many of us have got to “get stuff done” – and many a longer-form project has been distracted and derailed by YouTube, Facebook, and other smaller knowledges.

The article draws on one of my theories regarding productivity and machines of work.  The history of machines is dominated by unitary, task-focused devices (see Cohen’s Social History of American Technology for a review of discourses surrounding early technologies).  Even though industrial devices were technically collaborative, the focus of use was primarily individual and task-focused.  Fast forwarding to the creation of knowledge industries, we see a long lineage of restriction and task-focusing (i.e. working on computer systems with limited programs, no access to the internet).

Following Latour’s interpretation of Machines in Science in Action, the meaning we attribute to devices is socially constructed and situated.  The problem we face with “computers” is their many “constructions” and “situations.”  Our computers exist as boundaries between work and personal culture, hot and cold media, work and enjoyment, social and contractual obligation.  Our expectation that the computer remain a device of work is a discursive construction, and our perspective that it is a failing to be distracted by computers is a statement of values.

So why does Freedom work?  At a very practical level, yes, it removes the distraction of others, YouTube, Facebook, and so on.  But it also reshapes the device, reconfiguring our expectations of the device.  Is a computer running Freedom still a computer?  And that, I believe, is the power.  When the expectations are reconfigured and the device is reappropriated, we can approach it on new terms.

• 10/27 – Carolina College of Lifelong Learning (Small fee, but I am donating my time)
• 10/30 – NWS Summit “Visionary Talk” (Closed)
• 10/30 – Presenting some new research at the UNC Doctoral Student Symposium (multilevel and survival models of Facebook use – open to public)
• 11/2 -  I’m the fall speaker for UNC Greensboro’s University Libraries/LIS Lecture.  (Open to public)
• 11/5 – Guest lecturing INLS 200

Then I’m off to ASIST (Vancover, BC) were I’ll be talking about:

• “The Supportive Behaviors of Older Social Network Site Users” (with V. Stull and C. Thompson) at SIG-SI
• “Social Network Sites and Information Seeking During a Life Transition” at SIG-USE

I’ll also be interviewing for faculty positions while at ASIST – send any advice or leads my way!  Thankfully, the semester quiets down after ASIST, and I can look forward to a December full of writing and college basketball.

I was busy at AOIR, attending the doctoral colloquium (my last as a student), and giving two talks.  The first talk was a paper, entitled “Boundary Regulation in Social Media.”  This is work Woody Hartzog and I collaborated on, in which we interviewed people who maintain multiple, separate profiles on social network sites.  We were interested in learning about how these folks use multiple profiles as a boundary regulation strategy.  This research highlights a number of issues many of us are experiencing with context merging – as our friends, family members, coworkers and past friends merge into a single social network.  I’ve posted the slides below:

The second talk was out of some research-in-progress exploring the adoption of social networks by older users.  Over the past year, the largest growth sector in social networking has been the 35+ demograpic.  In our research, we talked to people in their 40’s, 50’s, 60’s and 70’s about their use of social network sites.  This was fascinating research, and learning about some of the challenges of reconnection via SNS after 30, 40 or even 50 years was particularly interesting.  As I mentioned, this is research in progress – which I’m conducting with Cheryl Thompson and Valeda Stull – and it involves a mix of methods and components.  Our next step is to implement a survey that builds on our findings.  You can see the slides below:

As for general themes for the conference, I admit I stuck pretty close to the social media/networking/privacy talks, but some general observations:  First, context is big.  Lots of researchers are looking at the effect of context on disclosure behavior.  Context has big practical implications for social networking sites, and both of my qualitative studies reveal that the big sites have lots of work to do to address these needs.

Second, mass reconnection is an interesting byproduct of the “democratization” of social networks (as Amanda Lenhart described.)  Reconnection was absolutely driving the use of social networks among the older users we interviewed.  Before SNS, reconnection was a costly and inefficient process; I think we can argue that the particular affordances of SNS (search, articulated networks) facilitate reconnection, and that reconnection is going to drive use of SNS for some time.  Of course, we must remember that the SNS is just the medium for reconnection, and that the “infrastructure” of reconnection relies on increasing broadband adoption, cheaper computers, and increasing technical literacy.

This goes without saying, but Twitter was a hot topic at AOIR.  I particularly enjoyed the work of danah boyd and Alice Marwick, who conducted a series of studies on Twitter this summer at Microsoft Research.  Alice’s talk was focused on the production of celebrity and microcelebrity in Twitter, and was just fascinating.  danah expanded this research, expanding how “teens are Twittering.”  Indeed, teens are a marginal segment of Twitter, with sparse networks, but what was particularly interesting is how they were using celebrity to create vectors for conversation, bridging networks and building relationships.  Very impressive research from both.

Of course, there were lots of great presentations at AOIR, too many to mention here.  I would like to particularly thank Heather Attig, Amanda Lenhart and Sarita Yardi, who were my co-panelists on the Late Adopters panel.  I really liked how this panel came together, bridging a variety of research questions and methods to provide insight into this phenomenon.  I’ll leave you with the slides from Amanda’s presentation, which provide some brand new topline data on Adult SNS use (47%).

Oh yes, if you want copies of the papers, I’ll be happy to email them to you. I’m not posting them right now because some are either under review, or being revised for journal submission. Just drop me a line.

“One Mac app that has found a way to solve this problem is called Freedom, which blocks all of your computer’s networking functions for a pre-determined number of minutes. In other words, once you set it, you’ve got no Web, no instant messaging, no e-mail — and the only way to undo Freedom’s block before the time runs out is to restart your machine.”

Freedom also garnered a mention on Mashable, in a post on 20 productivity tools for Mac users:

“Sometimes the Internet is more of a distraction than it is a productivity aid. For those times, the best solution is just to unplug. Freedom will turn off your Mac’s networking card for up to 8 hours, so you can get what you need to get done done, without the distraction of Facebook, Twitter and the latest viral videos.

Obviously, as a web writer, this doesn’t really work for me during the work week, but it’s great for when I’m on a deadline — like trying to finish an article of 20+ Mac productivity tools!”

This was cross-posted to the Freedom blog (http://macfreedom.com).

In the most extensive such analysis to date, David Yeager and Prof. Jon Krosnick compared seven non-random internet surveys with two others based instead on random or so-called probability samples. The non-probability internet surveys were less accurate, and customary adjustments did not uniformly improve them.

While the random-sample surveys were “consistently highly accurate,” the internet surveys based on self-selected or “opt-in” panels “were always less accurate, on average, than probability sample surveys, and were less consistent in their level of accuracy,” the researchers said. Further, they said, adjusting these samples to known population values had no effect on accuracy (and in one case even worsened it) as often as that process, known as weighting, improved it.

Also noteworthy:

While this paper is the first to evaluate the subject in such detail, intimations of these problems were posted in a blog item this summer by Reg Baker, COO of the research firm Market Strategies International. Estimates of smoking prevalence were similar in three probability samples, he reported, but less similar – with variation of as many as 14 points – in 17 opt-in online panels. In such panels, he said, “the results we get for any given study are highly dependent (and mostly unpredictable) on the panel we use. This is not good news.”

Yeager and Krosnick, meanwhile, provide one more eye-opener: The average highest weight for any one respondent across the opt-in online samples was 30 – one respondent, that is, standing for the equivalent of 30 in the full dataset. (And one went as high as 70.) The highest weights in the two probability samples, by contrast, were 5 and 8.

Nothing new or groundbreaking here, and yes, a little inside baseball, but relevant in the light of all of these web surveys showing that “Teens don’t tweet.”  First, convenience-sampled web surveys can’t offer standard errors, and the weighting process that produces errors is highly susceptible to inflation in areas where data are sparse.  This sparseness commonly occurs when studying the behavior of a low-response population such as young people, and is multiplied when studying an early-adopting phenomenon like Tweeting.

Langer’s blog is a worthwhile resource if you’re interested in survey methods.  And I hope to resume blogging – updating my syllabus, posting some recent papers, etc. – when I get a spare moment.

via Study Finds Trouble for Internet Surveys – The Numbers.

As these data will undoubtedly be reported breathlessly elsewhere, I thought it might be useful to step back and explore some of the issues with the methodology and conclusions.  So first, a note about the methodology.  The Nielsen NetView panel contains an impressive 250,000 users.  Metering software located on client machines records the websites visited by panel members.  A vast majority of the panel is recruited online; the panel is “calibrated” (weighted) against gold-standard sampling methods (Random Digit Dialing, etc.).

Survey weighting is a standard, fairly uncontroversial process.  It is commonly used and is thought of as preferable to census-type approaches that may systematically under-represent some populations.  However, reliable survey weighting gets tricky when the population is small.  Since teens are a notoriously hard-to-reach population, we generally see inflated standard errors around weighted teen respondents in a population survey.  Nielsen does not report standard errors, and the makeup of their panel is confidential, so therefore it is impossible to know how much error there is around the estimate of use.  If the panel is like other panels, though, there may be more error in young people than a high-response population, such as adults.  We’re very familiar with margins of error (the things you see in political polls, where error is reported as plus or minus 3 percent, etc).  An inflated error means the margin is larger, meaning that the estimate may vary by a larger amount.

This is not to put down Nielsen.  With 250,000 members, the panel likely has good coverage of young people.  Since my purpose is to use this example to critique web panels, we must point out two other issues.  First, bigger is not necessarily better if the sample is convenience driven.  Nielsen’s panel is very large, but simply because it is large doesn’t mean it is representative.  In fact, Nielsen is likely more interested in the larger size for better sparse-market coverage, as opposed to statistical reliability.  Second, the particular nature of recruitment into the main panel introduces selection bias.  If people aren’t selected randomly, then there may be characteristics of the population that covary with the variables of interest.  This is an omni-present issue with polling, but it must be noted.

So when we read a web poll of this particular nature, what are the critical questions we should be asking?  First, we should be concerned about cell size (the number of respondents) for a hard-to-reach population.  If young users are underrepresented, the standard errors on the estimates can be quite large (which may push an estimate around by +/- 10 percent).  We should also question the method of recruitment; if the majority of the panel comes in via the web, then who gets left out?  Since this poll is designed to represent online users, it is seems likely that heavy web users are participants (my guess).  But what if Twitter users actually aren’t like heavy web users?  There are a whole host of other questions we should ask regarding polls (response rate, sampling frame, etc) that generally aren’t answered in online polls.

It is important to understand the potential methodological issues when reading research.  Nielsen’s methods are standard for the industry, and they acknowledge the drawbacks and limitations.  In my opinion, the major problem isn’t the methods component, it is Nielsen’s spinning/presentation of its results.  In the Nielsen study (and the previous Participatory Media Network study), the findings focus on lack of teen use of Twitter.  However, the findings reported by Nielsen cover the following age ranges: 2-24, 25-54 and 55+.  The critical category, 2-24, covers a wide range of users – incredibly young children, adolescents, teens and adults.  The grand mean reported by Nielsen is affected by variation inside the different age categories.  Using census data, we can look at age breakdown over the ranges 2-24.  According to census, there are 80MM Americans under age 24 (0-24).  There are approximately 15-16MM Americans in the age ranges 0-4, 5-9, 10-14, 15-19, and 20-24.  Therefore, each category is pretty much weighed equally.  So lets (hypothetically) assume that no one age 0-9 uses Twitter, 5% of people age 10-14, 35% of people age 15-19, and 40% of people age 20-24 use Twitter.  To calculate the grand mean we would weight the percentages and then sum.  Such a formulation would give us 16% use for the demographic age 0-24 (0+0+.01+.07+.08).

The second problem with Nielsen’s presentation is the comparison range.  Comparing the age ranges 2-24 and 25-54 is not fair on a number of levels.  The first category can really only meaningfully cover age 13-24, while the 25-54 age range meaningfully covers 30 years.  If we weigh the estimates (16%/64%) by volume coverage (1:3 ratio), then the category volume for older users would be ~21% (I didn’t bother to weigh by census, just an estimate).  And what if we compared just teens against an adult category – we might even find that teens Twitter more than adults.  Keep in mind, with all the advantages afforded to older users (no Internet restrictions, etc) there are major differences between older users and teen/young users in their capacity to partake in online community.

My analysis is simplistic and speculative, but in certain configurations, “young people” could plausibly use Twitter at higher rates than “adults.”  I don’t have a guess regarding what is right, but my gut tells me that if Nielsen was more upfront regarding their sampling, and less misleading with their infographics, we’d have a different story.  And that story would not be as catchy and headline-grabbing as “Teens Don’t Tweet.”

I am beginning a new research project that will look at older, recent adopters of social networking sites (the fastest-growing population on many sites). I am interested in how these users are using the sites, what motivated them to join, and how the sites benefit and affect their daily lives. The first part of the study involves in-depth interviews, for which I am currently recruiting participants. More information:

UNC-Chapel Hill researchers are conducting a study of recent adopters of social networking sites (Facebook, Myspace). We seek individuals, age 40 or older, who first joined a social networking site within the last two years. If you meet these criteria, we are interested in talking to you about why you joined the social networking site and what you do on the site.

To qualify for this research, you must be age 40 or older and have started using social networking sites within the last two years. Your participation is entirely voluntary. Individuals who wish to participate will be interviewed for one hour, and they will fill out a simple questionnaire. Participants will be compensated $10.00 for their time. Interviews can be in person, or remotely (over the phone, via Skype, etc.). To volunteer for participation, or ask any questions about the project, please email Principal Investigator Fred Stutzman at fred@fredstutzman.com. If you prefer, you may call 919-260-8508.

This research has been approved by the University of North Carolina Institutional Review Board, IRB-09-1303. Gary Marchionini, Ph.D., Cary C. Boshamer Distinguished Professor in the School of Information and Library Science, is faculty supervisor of this study.

Please feel free to pass this along to anyone who you think might be interested. If you are interested in this project, I am currently seeking a research assistant to help with transcription and analysis. This is a great job for a Master’s-level student looking for topical research experience.

To date, no one has come up with a reliable algorithm for “coolness,” (which might explain why Facebook fought the buzz behind Twitter by, um, copying it). But for academics like Stutzman and others increasingly turning their attention to social networks, there’s a name for what happens when everyone joins the same site at the same time, perhaps rendering it uncool: “context collapse.” That’s the term used to describe a series of awkward events like when your boss or parents friend you, or someone posts a picture of you that you don’t want your colleagues seeing, or when an elementary school bully from your past starts commenting on your status updates. As these activities cascade, social media research has shown that people begin to shy away from their online persona and begin aggressively limiting the information that appears about themselves. Not surprisingly, users begin to stress out about their tangled social scenes and abandon the network all together. “What needs to happen—and what’s going to happen—is that there needs to be more granular privacy settings,” says Nicole Ellison, who researches and teaches on social media at Michigan State University. “So I can share a status update, but one I only want to go to my high school friends.”

As a side note, this has to be one of the fastest primary-research-to-Newsweek jumps ever.  We were interviewing dual-boundary maintainers in the morning, talking to Newsweek in the evening, and it was on the web the next day.  As a side note, we’re very close to wrapping up our dual-boundary research, and it has been fascinating.  Looking forward to presenting our conference paper at AOIR.