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Look at your phone. Go on, look at it. What is it?

It’s a clock. It’s a text-messaging glass slab. It’s a dynamically updating map/tracking device. It’s a ticket. It’s a late-night magazine. It’s an alarm clock. It’s a camera, photo album and publishing platform. It’s a gaming device, newsfeed(s), and a tether keeping work with you 24 hours a day.

Your laptop: it’s forty tabs open at once, word processing documents, music libraries (if you’re old), an EVEN BETTER gaming device, a TV and movie-watching platform, an audio editing suite, and, uh, other forms of entertainment.

You use these devices for dozens of different purposes, out of convenience and functional capacities. What I want you to think about is who you are in each of those purposes, and for whom you are in those purposes.

One of the most intriguing findings from my dissertation research (read it! become a member of a tiny club!) lo these four years ago was the degree to which students segregated audiences by medium. As I put it, they “use different communications technologies in their interactions with social, familial and academic audiences, in part as a manner of combatting the context collapse taking place on social network sites and mediated communications generally.” More directly: they talked to their friends via text message and Facebook message, called their parents on the phone, and only and ever talked to their professors in person and via email. That was, as they say, interesting, and something worthy of further study.

Well: I didn’t. But while the particular practices have shifted in the intervening time, these behaviors are no less intriguing or worthy of study and contemplation.

Cross-medium behavioral research is rare for a number of reasons. It’s expensive, difficult, time-consuming, methodologically fraught, ethically fraught. But I think the main limiting factor is that in any given moment, the incentives for any organization or individual performing research is to answer their central questions, as quickly/cheaply as possible. For an advertising firm: how did a given campaign deliver on KPIs as promised to the client? For an academic researcher: how does X behavior impact on my hopefully-tenure-securing line of research? For a membership organization: what were the A/B test results on a fundraising solicitation?

And to be crystal clear, this is NOT a problem solved by “Big Data.” Few but the most world-spanning organizations have the capacity to iteratively formulate hypotheses, expand data collection across boundaries, and act on findings. And the evidence suggests that even those world-spanning organizations don’t really know what to do with their endless reams of data. But, really, that’s neither here nor there: if you aren’t inside one of the world’s larger walled gardens of behavioral data, you’re still left with the same question. Namely: just who are your users, and who (and when, and how) are you to your users?

I am going to start examining this question over a series of posts here, identifying the scope of the issues, and the beginnings of how you might begin to address them at any given level of organization. Research in certain aspects of these issues has certainly exploded over the past years, so let me know what else you think I should read and incorporate. However, I’m not seeking to re-write my dissertation here: what I instead want to do is establish a basic functional understanding, based in practice and theory, of the kinds of balances struck by people managing the many channels of communication and content in their everyday lives.

Issue 1: Attention

One of the foremost issues is attention. There are two ways of looking at attention: as something to maintain, and as something to be acquired. From your perspective, dear reader, you of course want to maintain sustained attention – on relationships, on work, on engaging culture. An advertiser, on the other hand, wants to capture your attention. Chartbeat – which makes a fantastic suite of products for publishers, that I’ve used and enjoyed – is part of a tech vanguard that recognizes this. As they put it:

Online publishers know clicks don’t always reflect content quality.

But research shows more time spent paying attention to content does.

Advertisers know click-through rates don’t matter for display or paid content.

Research shows 2 things matter for getting a brand’s message across: the ad creative and the amount of time someone spends with it.

The Attention Web is about optimizing for your audience’s true attention.

From their perspective, attention equals quality, and a shift to focusing on quantifying attention means better quality content (oh and also more clients). It’s a compelling thesis – but then, it is your attention that they’re selling, to advertisers. Others are more interested in selling your attention to, well, you:

As our computing devices have become smaller, faster, and more pervasive, they have also become more distracting. The numbers are compelling: Americans spend 11 hours per day on digital devices, workers are digitally interrupted every 10.5 minutes, with interruptions costing the U.S. economy an estimated $650 Billion per year. That’s a lot of distraction.

Device makers have largely turned a blind eye to this issue, building distractions in to the very devices we need for work. We address this challenge with tools that simply and effectively reduce digital distractions. Our software interrupts the habitual cycle of distraction associated with social media, streaming sites, and games.

Attention is basically an adversarial dynamic: your devices and the advertiser-supported content therein yelling at you while you struggle to maintain concentration. Many or most of us are in this stage of managing our relationships with digital communicative prostheses – a struggle. It’s not a struggle without benefits, but nor is it one without costs – study after study shows the costs to both productivity and personal health and well-being of a consistently-interrupted existence.

A central part of this struggle is creating a hierarchy – either explicit or implicit – of attention. When do you respond to a text message? It depends when you receive it, and from whom. Do you return an email? Again: who sent it, work or personal, when did it get received? And then: what do you read, or listen to? That also depends – how did you get there? A link from a friend, an immediately-forgotten source on your social media timeline, through a series of unreproducible clicks? The depth, length, and quality of the attention devoted depends on all these factors and more – but I believe it’s impossible to understand the meaning of a given interaction without looking at how these hierarchies are created. I’ll do that in my next post.

Big Data and Foxes

Earlier this week I went to an excellent discussion put on by danah boyd and her Data & Society Research Institute, entitled “Social, Cultural & Ethical Dimensions of ‘Big Data.’” Right off the top, I have to give major kudos to danah for organizing a fantastic panel that incorporated a great combination of voices – who, not for nothing (indeed, for a lot) were not just a bunch of white dudes (only one white dude, in fact) – from across different disciplines and perspectives. I’ll do a brief play-by-play to set the table for a couple of larger thoughts.

Following a rigorously on-message video from John Podesta and fairly anodyne talk (well, except for this) from Nicole Wong from the White House Office of Science and Technology Policy, danah led off with introductory remarks and passed off to Anil Dash, who served excellently as moderator (mostly by staying out of the way, as he made a point of noting). Alondra Nelson from Columbia University was first up, giving an account by turns moving, terrifying, and engaging on the state of play and human consequences flowing from DNA databases – both those managed by law enforcement and the loopholes that allow privately-managed data repositories to skirt privacy protections. She was followed by Shamina Singh from the MasterCard Center for Inclusive Growth, who provided several on-the-ground examples of working with governments, NGOs, and poor people to more efficiently deliver social benefits. In particular, she focused on a MasterCard program to provide direct transfers of cash to refugee populations, cutting out the vastly inefficient global aid infrastructure network.

Singh was followed by Steven Hodas from the New York City Department of Education, who laid out an illuminating picture of the lifecycle of data in education systems, the ways in which private actors subvert and undermine public privacy, and – not just a critic – offered a genuinely thought-provoking new way of thinking about how to regulate dissemination of private information. The excellent Kate Crawford batted cleanup, discussing predictive privacy harms and what she called “data due process.” Dash facilitated a very long and almost entirely productive audience question and discussion session (45 minutes, at the least), and I left with many more things on my mind than I entered with. I’d had the privilege of listening to eight different speakers, each from a background either subtly or radically different from one another. Not once did a speaker follow another just like them, and no small value came in the synthesis from those differing perspectives and those of the audience.

This week also saw the relaunch of FiveThirtyEight.com under its new ESPN/Disney instance. It was launched with a manifesto from founder Nate Silver, entitled “What the Fox Knows,” which is a bit meandering but generally comes down as setting FiveThirtyEight as opposed to both traditional journalism and science research, based on some fairly blithe generalizations of those fields. What it doesn’t quite do, oddly for a manifesto, is state just what FiveThirtyEight is for other than a sort of process and attitudinal approach. Marx (or even Levine/Locke/Searls/Weinberger) it ain’t.

Silver has come in for no small criticism, and not just from his normal antagonists. Emily Bell laid out the rather less-than-revolutionary staffing makeup of the current raft of new-media startups, led by Ezra Klein, Glenn Greenwald, and Silver. And Paul Krugman detailed some rather serious concerns about Silver’s approach:

you can’t be an effective fox just by letting the data speak for itself — because it never does. You use data to inform your analysis, you let it tell you that your pet hypothesis is wrong, but data are never a substitute for hard thinking. If you think the data are speaking for themselves, what you’re really doing is implicit theorizing, which is a really bad idea (because you can’t test your assumptions if you don’t even know what you’re assuming.)

These two critiques are not unrelated. Bell called out Silver for his desire for a “clubhouse,” and rightly so, because groupthink clubhouses – whether of insiders or outsiders – are the most fertile breeding grounds for implicit theorizing. Krugman revisited and expanded his critique, saying:

I hope that Nate Silver understands what it actually means to be a fox. The fox, according to Archilocus, knows many things. But he does know these things — he doesn’t approach each topic as a blank slate, or imagine that there are general-purpose data-analysis tools that absolve him from any need to understand the particular subject he’s tackling. Even the most basic question — where are the data I need? — often takes a fair bit of expertise.

Which brings me around to the beginning of this post. The value in Monday’s discussion flowed directly from both the diversity – in professional background, gender, ethnicity – and the expertise of the speakers present. They each spoke deeply from a particular perspective, and while “Big Data” was the through-line connecting them, the content which animated their discussion, approach, and theorizing was specific to their experience and expertise. The systems that create data have their own biases and agenda, which only discipline-specific knowledge can help untangle and correct for. There is still no Philosopher’s Stone, but base metals have their own stories. Knowing their essential properties isn’t easy or quick, but little is easy that’s of lasting and real value.

There’s been a lot of hyperventilating over the recent news that Green Mountain is going to start cracking down on competitors designing coffee pods for their gross coffee makers:

With its single-serving coffee pods, Green Mountain Coffee has transformed the business of brew. Pop a capsule into one of the company’s Keurig machines, and the machine will instantly churn out your daily caffeine dose.

But Green Mountain doesn’t want copycats taking the business it pioneered away. That’s why CEO Brian Kelley says its new coffee makers will include technology that prevents people from using pods from other companies. The approach has been compared to DRM restrictions that limit the sharing of digital music and video online. But more than just curbing your coffee choices, Green Mountain’s protections portend the kind of closed system that could gut the early promise of the Internet of Things — a promise that hinges on a broad network of digital, connected devices remaking the everyday world.

Cory Doctorow thinks it’s a bridge too far and might end up promoting a backlash, or that Green Mountain’s overzealousness might end up with good court rulings against them. Dan Gillmor isn’t bothered by the coffee pods per se but takes a rather grander tone in conclusion:

We’re still in the early days of this war – and make no mistake, that’s what we face. The interests that want control over our lives and pocketbooks are wealthy and powerful. People are waking up to the threat. Now we all need to fight back.

I don’t disagree with either, really, but am a bit more sanguine in general, because of Microsoft Windows.  Windows might be a bit of a punchline these days, but I’m old enough to remember when it was an existential threat to commerce and resulted in one of the biggest antitrust cases ever. Though the ruling ended up going against Microsoft, the remedies were, through our current view, pretty minor. There were no Baby Bills, and Microsoft continued to have a crushing monopoly on the operating system and office productivity suite market, and make money hand over fist.

And then… the world changed. Microsoft continued to fundamentally misunderstand the Internet, and Apple managed not to go out of business and then became the plucky underdog and then the one of world’s most profitable corporations. Google won the search wars and then started eating everything remotely related (and not) in sight; Facebook was the best/last SNS. And Microsoft still had a massively profitable near-monopoly on the operating system and office productivity suite markets. The Beige Eminence of Redmond continues to have a massive role in day-to-day life around the world, often in problematic ways. But the last 15 years of tech history have shown that despite market control and massive profits, Microsoft cannot shape events entirely to their liking. They were chastened by U.S. v Microsoft, sure, but remain far more chastened by the fact that Internet Explorer and Bing are terrible and nobody likes them. Billions of person-hours are spent annually in computers with Microsoft OSes and in Word and Excel – but that hasn’t changed the fact that Microsoft cannot understand at a very basic level, the things that people spend most of their time doing on computers.

So: coffee pods. Coffee pods were a good idea as a response to legitimately terrible/inconsistent office coffee; to people who like coffee but don’t think about it too much and like not having to clean up coffee grounds (but seriously people, COMPOST, that is some good compost there); and a clever dumbed-down cashing-in on wider use of espresso machines. I briefly worked a job where the office had one – that was great, because otherwise the coffee would have been worse-than-mediocre, in all likelihood; I like it when I stay in a hotel and there’s a coffee pod machine there. But I’ve never for a second considered getting one, myself.

But mostly, coffee pods are a cheap plastic mediocrity, a Beige Eminence which performs the task of producing coffee product with little thought nor distinction. The principle of defending markets from monopolistic domination is important within a system of regulated capitalism (see: US broadband access), but in this case, what is the principle really defending? The opportunity for other suppliers to make a slightly-thinner margin on a mediocre way of delivering coffee to office workers and lazy suburbanites? And there are plenty of other coffee pod standards. It’s also not as if there’s any lack of ways to make – much better! just as easily! – coffee. Or tea. Green Mountain’s power play is, ultimately, a small-time move that doesn’t really impact important innovation in coffee delivery systems. It’s also a natural impulse and end result of our particular market system, and isn’t really worth worrying about until and unless a number of lawsuits that haven’t happened yet have bad results.

The Death of Comments

I don’t know if this quite qualifies as a trend, but then, trend pieces don’t need real facts, so what the hey. Something I’ve noticed these last months across several major sites, is a move away from the traditional, boring-but-understood approach to comments. While pretty much everyone already agreed that YouTube comments were the worst thing on the Internet, somehow Google managed to make them worse. Not more misogynistic, homophobic, racist, or violent – that’d be hard – but far more nonsensical. In necessitating a Google+ account (which, mea culpa, continues to be totally useless), it shut out many, and in re-threading the conversations based on “relevance” it took away the free-wheeling (often awful, but still) conversational threads of comment sections.

Similar complaints have followed on Gawker’s transition to Kinja, but perhaps the most ridiculous post-comment context has to be Voice Media Group’s new “My Voice Nation” system, which I was alerted to after it pulled in a second-order @ exchange I’d had about one of its stories. Not the tweet itself, but the conversation I’d had about the tweet, with a friend. The “comment section” thus becomes a random mash of unrelated, unconnected words – a documentation of buzz, perhaps, but in no ways a conversation.

And of course: I never signed up for that. I did send that tweet, yes, and I suppose that’s public-ish, but again – not all publicly accessible data is meant to be publicized. I’m guessing most people won’t ever notice, but for me, I’ll just make sure to never send out or comment on a piece of Voice Media Group content unless it’s unavoidable (which is to say: never).

What’s curious about this Death of Comments is that they’re not being eliminated as a feature for principled reasons, or as a straight cost-benefit analysis (i.e., it doesn’t really make sense to have a community manager paid to make the comments not *quite* so execrable). Rather, the transition seems to be away from comments and towards a comment-like substance – words related to the content, written at some point in some medium, presented in some relation to the content. I’m not sure what the long game is on that, but it’s all a little lorem ipsumy for my taste.

Following on news from the Guardian that Facebook saw a nearly 2% decline in active UK users over the holidays, I thought I’d briefly cover some of the implications of this news, from my perspective.

  • Obviously this has been coming for quite a while in core markets. As the Guardian notes, in the UK Facebook has 53% market penetration, second only to the US at 54%; in terms of gross users, the US has 169M, Brazil 65M, India 63M. Clearly the play is hoping on further expansion in the latter two markets – but that proposition is tenuous, both because the of the fast-growing but still-smaller middle classes there, and because,
  • Facebook still doesn’t get mobile. Its apps are still only-OK in terms of usability, and as witnessed by the Instagram terms-of-service clusterfcuk – which resulted in more than 50% decline in users – Facebook has a fairly poor understanding of the mobile user. Which is especially unfortunate for its future expansion in emerging markets – e.g., Brazil, India – as connectivity there is primarily through mobile devices, and not desktops.
  • Facebook as public company has always been a questionable proposition, as its whole model of ad-rate-growth-driven-by-traffic-growth-driven-by-user-growth is inherently untenable given that… at a certain point you run out of users. Also, the fact that every social network site so far has seen long-term time-on-site decline from its core users. Basically: if you’ve been shorting $FB, you’ve got to be feeling pretty good right now.
  • Facebook as social utility isn’t going anywhere anytime soon. Too many people, content providers, websites, and the general infrastructure of the Web have too much locked in for that to happen. But there are various ways that it can evolve from here. I’m still convinced that long-term there will be a competitive market for identity hosting, and that Facebook’s best move is to get in front of that in both setting open standards and providing a premium service; but we shall see.

     

I wrote a column for the Txchnologist, and it’s over here. If you like what I’ve been writing about here recently, you’ll like this too. A preview:

Social media, despite its centrality in our daily lives, still causes most businesses to tremble with fear. They fear liability over what employees may post in their official capacity. They fear embarrassing information posted by employees, both current and potential, in their off hours. They conduct social media “background checks” to ferret out anything that might reflect poorly on the business. Such is this fear that social media sites are discouraged or outright blocked at many workplaces.

As modes of business communication, social media channels are treated as loudspeakers, with messages painstakingly cleared through legal and public relations, polished to perfect sheen and void of real meaning. Meanwhile, email remains the central trusted tool of business communications. Used internally, it is the official channel for directives, meeting planning and document-sharing. It is the central way to communicate anything that matters both within your organization and to any collaborators. For external communications, email lists are built, maintained and bombarded. Huge marketing dollars are spent formulating email segmentation strategies, word-smithing, and tracking open rates.

All of this is entirely backwards.

Read the whole thing!

Having had a few weeks to digest both my initial thoughts on Google+ and the experience of actually using it, I thought I’d step back and offer a 30,000-foot-view of where I think things are, and are going, in this space.

First: Google+ is still pretty nice, even if it doesn’t quite know what it is. That’s fine! It’s been a month in psuedo-beta, and has 10M users. What I think the larger picture is here, is this:

Email is dying. Smart people are helping kill it. Google understands this, and that gMail is at this point a continually depreciating asset (something MSFT never recognized about Hotmail). Google+ is among other things, about providing gMail users a bridge to a post-email digital social space with minimal transition costs (always the biggest barrier to entry for a new social service). The social graph is already built into gMail users’ contact lists – Google+ is just about bootstrapping a different interface onto it.

There are real privacy concerns about Google+, and the mass deletion of accounts shows that Google is still struggling with psuedonymity. But long-run, the proposition is clear for both Google and its users.

Let me backtrack and say that I don’t think email will die, exactly, but rather become a mode of communication used for some things, sometimes, but not everything all the time. Physical mail, similarly, isn’t disappearing anytime soon (well not until 3D printing really scales up), and while telephony might be wearing different hats these days (i.e., mobile and digital rather than locked-position and analog), the fundamental dynamics are the same.

What we’re seeing is a rationalization of communications mediums, with people – young people especially, who don’t have the cruft of legacy communications patterns built on top – only using what makes sense for a given use, at a given time. For quick and short communications, this means text messaging – and given the shift in mobile plans towards offering unlimited texting, this doesn’t make anyone money, because save for the NSA and NewsCorp, nobody’s scanning and indexing your text message for relevant advertising content. Likewise, the efforts of both Facebook and Google to incorporate SMS into their user interfaces just haven’t caught on – why make the easiest way of communicating less easy?

Advertisers don’t know how good they’ve got it right now – despite click-through rates of at best 0.1% on banner ads, they’ve never known more about their target audiences for less money. From here on out, as more and more communication moves from the public social web and indexable email back to a range of peer-to-peer communications (TXT, telephony, video chats), it’s only going to get more and more expensive to know what people are thinking and talking about.  Because you’re going to have to actually ask the people.

This is why it’s a shame how comparatively little institutional support there’s been – and how slow IRBs have been in addressing the pace of online user research – for research around online sociability (no sour grapes here though! SILS is kicking butt!). Apart from the great work of a relatively small cohort of pioneering researchers who’ve been gathering data when and how they can this last decade, we’ve just lost a lot of data: those questions that went unasked, data went unscraped. And when perceptions of an interface aren’t asked in the moment, it’s not just gone, it’s gone-gone – who can remember what Facebook looked like 18 months ago?

But this is also an opportunity. Going forward into a world of multi-channel communications presents a fascinating set of new questions not just about why thus-and-so interface creates certain effects, but what people want to do, and how they realize those desires in different contexts. This is changing constantly, and shows no sign of slowing down. The real opportunity is to build on what we as researchers (both academic and market-oriented) already know about online sociability by asking questions focused not on the vagaries of changing interfaces and services, but rooted in the first principles of how people use communications technology. When we can keep asking those same questions over time – building real longitudinal data that can take into account the ebb and flow of seasons and services – we will build from knowledge to understanding. And when we understand, we can become the masters of our technologies, not the other way around.

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