What I see here is an ecosystem. There are narrow real-time feeds such as expertly curated Twitter accounts, and big general reference works like Wikipedia. There are armies of reporters working in their niches, but also colonies of computer scientists. There are curators both human and algorithmic. And I have no problem imagining that this ecosystem includes certain kinds of artists and artworks. Let’s say it includes all public acts and systems which come down to one person trying to tell another, “I didn’t just make this up. There’s something here of the world we share.”

I asked people what to call it. Some said “media.” That captures a lot of it, but I’m not really talking about the art or entertainment aspects of media. Also I wanted to include something of where ideas come from, something about discussions, collaborative investigation, and the generation of new knowledge. Other people said “information” but there is much more here than being informed. Information alone doesn’t make us care or act. It is part of, but only part of, what it means to connect to another human being at a distance.  Someone else said “the fourth estate” and this is much closer, because it pulls in all the ideas around civic participation and public discourse and speaking truth to power, loads of stuff we generally file under “democracy.” But the fourth estate today means “the press” and what I want to talk about is broader than journalism.

I’m just going to call this the “digital public sphere”, building on Jürgen Habermas’ idea of a place for the discussion of shared concerns, public yet apart from the state. Maybe that’s not a great name — it’s a bit dry for my taste — but perhaps it’s the best that can be done in three words, and it’s already in use as a phrase to refer to many of the sorts of things I want to talk about. “Public sphere” captures something important, something about the societal goals of the system, and “digital” is a modifier that means we have to account for interactivity, networks, and computation. Taking inspiration from Michael Schudson’s essay ”Six or seven things that news can do for democracy,” I want to ask what the digital public sphere can do for us. I think I see three broad categories, which are also three goals to keep in mind as we build our institutions and systems.

1. Information. It should be possible for people to find things out, whatever they want to know. Our institutions should help people organize to produce valuable new knowledge. And important information should automatically reach each person at just the right moment.

2. Empathy. The vast majority of people in the world, we will only know through media. We must strive to represent the “other” to each-other with compassion and reality. We can’t forget that there are people on the other end of the wire.

3. Collective action. What good is public deliberation if we can’t eventually come to a decision and act? But truly enabling the formation of broad agreement also requires that our information systems support conflict resolution. In this age of complex overlapping communities, this role spans everything from the local to the global.

Each of these is its own rich area, and each of these roles already cuts across many different forms and institutions of media.

Information
I’d like to live in a world where it’s cheap and easy for anyone to satisfy the following desires:

1. “I want to learn about X.”
2. “How do we know that about X?”
3. “What are the most interesting things we don’t know about X?”
4. “Please keep me informed about X.”
5. “I think we should know more about X.”
6. “I know something about X and want to tell others.”

These desires span everything from mundane queries (“what time does the store close?”) to complex questions of fact (“what will be the effects of global climate change?”) And they apply at all scales; I might have a burning desire to know how the city government is going to deal with bike lanes, or I might be curious about the sum total of humanity’s knowledge of breast cancer — everything we know today, plus all the good questions we can’t yet answer. Different institutions exist to address each of these needs in various ways. Libraries have historically served the need to answer specific questions, desires number #1 and #2, but search engines also do this. Journalism strives to keep people abreast of current events, the essence of #4. Academia has focused on how we know and what we don’t yet know, which is #2 and #3.

This list includes two functions related to the production of new knowledge, because it seems to me that the public information ecosystem should support people working together to become collectively smarter. That’s why I’ve included #5, which is something like casting a vote for an unanswered question, and #6, the peer-to-peer ability to provide an answer. These seem like key elements in the democratic production of knowledge, because the resources which can be devoted to investigating answers are limited. There will always be a finite number of people well placed to answer any particular question, whether those people are researchers, reporters, subject matter experts, or simply well-informed. I like to imagine that their collective output is dwarfed by human curiosity. So efficiency matters, and we need to find ways to aggregate the questions of a community, and route each question to the person or people best positioned to find out the answer.

In the context of professional journalism, this amounts to asking what unanswered questions are most pressing to the community served by a newsroom. One could devise systems of asking the audience (like Quora and StackExchange) or analyze search logs (ala Demand Media.) That newsrooms don’t frequently do these things is, I think, an artifact of industrial history — and an unfilled niche in the current ecosystem. Search engines know where the gaps between supply and demand lie, but they’re not in the business of researching new answers. Newsrooms can produce the supply, but they don’t have an understanding of the demand. Today, these two sides of the industry do not work together to close this loop. Some symbiotic hybrid of Google and The Associated Press might be an uncannily good system for answering civic questions.

When new information does become available, there’s the issue of timing and routing. This is #4 again, “please keep me informed.” Traditionally, journalism has answered the question “who should know when?” with “everyone everything as fast as possible” but this is ridiculous today. I really don’t want my phone to vibrate for every news article ever written, which is why only “important” stories generate alerts. But taste and specialization dictate different definitions of “important” for each person, and old answers delivered when I need them might be just as valuable as new information delivered hot and fresh. Google is far down this track with its thinking on knowing what I want before I search for it.

Empathy 
There is no better way to show one person to another, across a distance, than the human story. These stories about other people may be informative, sure, but maybe their real purpose is to help us feel what it is like to be someone else. This is an old art; one journalist friend credits Homer with the last major innovation in the form.

But we also have to show whole groups to each other, a very “mass media” goal. If I’ve never met a Cambodian or hung out with a union organizer, I only know what I see in the media. How can and should entire communities, groups, cultures, races, interests or nations be represented?

A good journalist, anthropologist, or writer can live with a community for a while, observing and learning, then articulate generalizations. This is important and useful. It’s also wildly subjective. But then, so is empathy. Curation and amplification can also be empathetic processes: someone can direct attention to the genuine voices of a community. This “don’t speak, point” role has been articulated by Ethan Zuckerman and practiced by Andy Carvin.

But these are still at the level of individual stories. Who is representative? If I can only talk to five people, which five people should I know? Maybe a human story, no matter how effective, is just a single sample in the sense of a tiny part standing for the whole. Turning this notion around, making it personal, I come to an ideal: If I am to be seen as part of some group, then I want representations of that group to include me in some way. This is an argument that mass media coverage of a community should try to account for every person in that community. This is absurd in practical terms, but it can serve as a signpost, a core idea, something to aim for.

Fortunately, more inclusive representations are getting easier. Most profoundly, the widespread availability of peer-to-peer communication networks makes it easier than ever for a single member of a community to speak and be heard widely.

We also have data. We can compile the demographics of social movements, or conduct polls to find “public opinion.” We can learn a lot from the numbers that describe a particular population, which is why surveys and censuses persist. But data are terrible at producing the emotional response at the core of empathy. For most people, learning that 23% of the children in some state live in poverty lacks the gut-punch of a story about a child who goes hungry at the end of every month. In fact there is evidence that making someone think analytically about an issue actually makes them less compassionate.

The best reporting might combine human stories with broader data. I am impressed by CNN’s interactive exploration of American casualties in Iraq, which links mass visualization with photographs and stories about each individual. But that piece covers a comparatively small population, only a few thousand people. There are emerging techniques to understand much larger groups, such as by visualizing the data trails of online life, all of the personal information that we leave behind. We can visualize communities, using aggregate information to see the patterns of human association at all scales. I suspect that mass data visualization represents a fundamentally new way of understanding large groups, a way that is perhaps more inclusive than anecdotes yet richer than demographics. Also, visualization forces us into conversations about who exactly is a member of the community in question, because each person is either included in a particular visualization or not. Drawing such a hard boundary is often difficult, but it’s good to talk about the meanings of our labels.

And yet, for all this new technology, empathy remains a deeply human pursuit. Do we really want statistically unbiased samples of a community? My friend Quinn Norton says that journalism should “strive to show us our better selves.” Sometimes, what we need is brutal honesty. At other times, what we need is kindness and inspiration.

Collective action

What a difficult challenge advances in communication have become in recent decades. On the one hand they are definitely bringing us closer to each other, but are they really bringing us together?

- Ryszard Kapuściński, The Other

I am sensitive to the idea of filter bubbles and concerns about the fragmentation of media, the worry that the personalization of information will create a series of insular and homogenous communities, but I cannot abide the implied nostalgia for the broadcast era. I do not see how one-size-fits-all media can ever serve a diverse and specialized society, and so: let a million micro-cultures bloom! But I do see a need for powerful unifying forces within the public sphere, because everything from keeping a park clean to tackling global climate change requires the agreement and cooperation of a community.

We have long had decision making systems at all scales — from the neighborhood to the United Nations — and these mechanisms span a range from very lightweight and informal to global and ritualized. In many cases decision-making is built upon voting, with some majority required to pass, such as 51% or 66%. But is a vicious, hard-fought 51% in a polarized society really the best we can do? And what about all the issues that we will not be voting on — that is to say, most of them?

Unfortunately, getting agreement among even very moderate numbers of people seems phenomenally difficult. People disagree about methods, but in a pluralistic society they often disagree even more strongly about goals. Sometimes presenting all sides with credible information is enough, but strongly held disagreements usually cannot be resolved by shared facts; experimental work shows that, in many circumstances, polarization deepens with more information. This is the painful truth that blows a hole in ideas like “informed public” and “deliberative democracy.”

Something else is needed here. I want to bring the field of conflict resolution into the digital public sphere. As a named pursuit with its own literature and community, this is a young subject, really only begun after World War II. I love the field, but it’s in its infancy; I think it’s safe to say that we really don’t know very much about how to help groups with incompatible values find acceptable common solutions. We know even less about how to do this in an online setting.

But we can say for sure that “moderator” is an important role in the digital public sphere. This is old-school internet culture, dating back to the pre-web Usenet days, and we have evolved very many tools for keeping online discussions well-ordered, from classic comment moderation to collaborative filtering, reputation systems, online polls, and various other tricks. At the edges, moderation turns into conflict resolution, and there are tools for this too. I’m particularly intrigued by visualizations that show where a community agrees or disagrees along multiple axes, because the conceptually similar process of “peace polls” has had some success in real-world conflict situations such as Northern Ireland. I bet we could also learn from the arduously evolved dispute resolution processes of Wikipedia.

It seems to me that the ideal of legitimate community decision making is consensus, 100% agreement. This is very difficult, another unreachable goal, but we could define a scale from 51% agreement to 100%, and say that the goal is  ”as consensus as possible” decision making, which would also be “as legitimate as possible.” With this sort of metric — and always remembering that the goal is to reach a decision on a collective action, not to make people agree for the sake of it — we could undertake a systematic study of online consensus formation. For any given community, for any given issue, how fragmented is the discourse? Do people with different opinions hang out in different places online? Can we document examples of successful and unsuccessful online consensus formation, as has been done in the offline case? What role do human moderators play, and how can well-designed social software contribute? How do the processes of online agreement and disagreement play out at different scales and under different circumstances? How we do know when the process has converged to a “good” answer, and when it has degraded into hegemony or groupthink? These are mostly unexplored questions. Fortunately, there’s a huge amount of related work to draw on: voting systems and public choice theory, social network analysis, cognitive psychology, information flow and media ecosystems, social software design, issues of identity and culture, language and semiotics, epistemology…

I would like conflict resolution to be an explicit goal of our media platforms and processes, because we cannot afford to be polarized and grid-locked while there are important collective problems to be solved. We may have lost the unifying narrative of the front page, but that narrative was neither comprehensive nor inclusive: it didn’t always address the problems of concern to me, nor did it ask me what I thought. Effective collective action, at all relevant scales, seems a better and more concrete goal than “shared narrative.” It is also an exceptionally hard problem — in some ways it is the problem of democracy itself — but there’s lots to try, and our public sphere must be designed to support this.

Why now?
I began writing this essay because I wanted to say something very simple: all of these things — journalism, search engines, Wikipedia, social media and the lot — have to work together to common ends. There is today no one profession which encompasses the entirety of the public sphere. Journalism used to be the primary bearer of these responsibilities — or perhaps that was a well-meaning illusion sprung from near monopolies on mass information distribution channels. Either way, that era is now approaching two decades gone. Now what we have is an ecosystem, and in true networked fashion there may not ever again be a central authority. From algorithm designers to dedicated curators to, yes, traditional on-the-scene pro journalists, a great many people in different fields now have a part in shaping the digital public sphere. I wanted try to understand what all of us are working toward. I hope that I have at least articulated goals that we can agree are important.

There is something extraordinarily rich in the intersection of computer science and journalism. It feels like there’s a nascent field in the making, tied to the rise of the internet. The last few years have seen calls for a new class of  “programmer journalist” and the birth of a community of hacks and hackers. Meanwhile, several schools are now offering joint degrees. But we’ll need more than competent programmers in newsrooms. What are the key problems of computational journalism? What other fields can we draw upon for ideas and theory? For that matter, what is it?

I’d like to propose a working definition of computational journalism as the application of computer science to the problems of public information, knowledge, and belief, by practitioners who see their mission as outside of both commerce and government. This includes the journalistic mainstay of “reporting” — because information not published is information not known — but my definition is intentionally much broader than that. To succeed, this young discipline will need to draw heavily from social science, computer science, public communications, cognitive psychology and other fields, as well as the traditional values and practices of the journalism profession.

“Computational journalism” has no textbooks yet. In fact the term barely is barely recognized. The phrase seems to have emerged at Georgia Tech in 2006 or 2007. Nonetheless I feel like there are already important topics and key references.

Data journalism
Data journalism is obtaining, reporting on, curating and publishing data in the public interest. The practice is often more about spreadsheets than algorithms, so I’ll suggest that not all data journalism is “computational,” in the same way that a novel written on a word processor isn’t “computational.” But data journalism is interesting and important and dovetails with computational journalism in many ways.

• The Nieman Journalism Lab’s interview with Guardian Data Blog editor Simon Rogers remains a solid introduction to (one kind of) contemporary practice.
• The best practical guides I know are Rogers’ “How to: get to grips with data journalism” and Dan Nguyen’s series of data-scraping tutorials at ProPublica.
• Stanford’s Journalism in the Age of Data is an hour-long documentary on data journalism and visualization.
• The web is a linked system of human-readable documents. Now Tim Berners-Lee wants to create a web of machine-readable linked data. The full potential is unclear, but it’s a big idea that may come to be the backbone of semantic web visions. The New York Times, The Guardian, and others are experimenting with open data APIs.
• Everyblock creator Adrian Holovaty seems to have been the first to suggest that reporters file structured data in his 2006 “A Fundamental Way Newspaper Websites Need to Change.” This idea is beautifully expanded in Stijn Debrouwere’s “Information Architecture for News Websites” series.

Visualization
Big data requires powerful exploration and storytelling tools, and increasingly that means visualization. But there’s good visualization and bad visualization, and the field has advanced tremendously since Tufte wrote The Visual Display of Quantitative Information. There is lots of good science that is too little known, and many open problems here.

• Tamara Munzner’s chapter on visualization is the essential primer. She puts visualization on rigorous perceptual footing, and discusses all the major categories of practice. Absolutely required reading for anyone who works with pictures of data.
• Ben Fry invented the Processing language and wrote his PhD thesis on “computational information design,” which is his powerful conception of the iterative, interactive practice of designing useful visualizations.
• How do we make visualization statistically rigorous? How do we know we’re not just fooling ourselves when we see patterns in the pixels? This amazing paper by Wickham et. al. has some answers.
• Is a visualization a story? Segal and Heer explore this question in “Narrative Visualization: Telling Stories with Data.”

Computational linguistics
Data is more than numbers. Given that the web is designed to be read by humans, it makes heavy use of human language. And then there are all the world’s books, and the archival recordings of millions of speeches and interviews. Computers are slowly getting better at dealing with language.

• Word frequency techniques like tf-idf and the vector space document model are very simple and very useful. See also stemming. Lots more in the wonderful (and free!) Introduction to Information Retrieval. This book explains how search engines are built, and  discusses tf-idf etc. in great technical detail.
• Statistical language models are increasingly important for all kinds of applications. Michael Nielsen has a great introduction to statistical machine translation. Google’s Peter Norvig discusses how he implemented statistical spelling correction on his laptop during a long plane flight. For the full deal, see the book Foundations of Statistical Natural Language Processing.
• On a related note, Google N-gram viewer lets you look at the frequency of short phrases within 4% of all books published, ever. The excellent paper gives examples of how to use this for cultural research. Dan Cohen has important criticisms.
• Speech-to-text algorithms enable automated transcription, and Matt Thompson explores the huge implications for journalism.
• Reuters maintains the OpenCalais entity extraction service, which parses text to contextually determine who and what is referenced.
• IBM’s Watson project built a question-answering system that reads reference books and wins at Jeopardy. Imagine how useful to journalists and curious readers this could be! This paper on the DeepQA system describes how they did it.

Communications technology and free speech
Code is law. Because our communications systems use software, the underlying mathematics of communication lead to staggering political consequences — including whether or not it is possible for governments to verify online identity or remove things from the internet. The key topics here are networks, cryptography, and information theory.

• The Handbook of Applied Cryptography is a classic, and free online. But despite the title it doesn’t really explain how crypto is used in the real world, like Wikipedia does.
• It’s important to know how the internet routes information, using TCP/IP and BGP, or at a somewhat higher level, things like the BitTorrent protocol. The technical details determine how hard it is to do things like block websites, suppress the dissemination of a file, or remove entire countries from the internet.
• Anonymity is deeply important to online free speech, and very hard. The Tor project is the outstanding leader in anonymity-related research.
• Information theory is stunningly useful across almost every technical discipline. Pierce’s short textbook is the classic introduction, while Tom Schneider’s Information Theory Primer seems to be the best free online reference.

Tracking the spread of information (and misinformation)
What do we know about how information spreads through society? Very little. But one nice side effect of our increasingly digital public sphere is the ability to track such things, at least in principle.

• Memetracker was (AFAIK) the first credible demonstration of whole-web information tracking, following quoted soundbites through blogs and mainstream news sites and everything in between. Zach Seward has cogent reflections on their findings.
• The Truthy Project aims for automated detection of astro-turfing on Twitter. They specialize in covert political messaging, or as I like to call it, computational propaganda.
• We badly need tools to help us determine the source of any given online “fact.” There are many existing techniques that could be applied to the problem, as I discussed in a previous post.
• If we had information provenance tools that worked across a spectrum of media outlets and feed types (web, social media, etc.) it would be much cheaper to do the sort of information ecosystem studies that Pew and others occasionally undertake. This would lead to a much better understanding of who does original reporting.

Filtering and recommendation
With vastly more information than ever before available to us, attention becomes the scarcest resource. Algorithms are an essential tool in filtering the flood of information that reaches each person. (Social media networks also act as filters.)

• The paper on preference networks by Turyen et. al. is probably as good an introduction as anything to the state of the art in recommendation engines, those algorithms that tell you what articles you might like to read or what movies you might like to watch.
• Before Google News there was Columbia News Blaster, which incorporated a number of interesting algorithms such as multi-lingual article clustering, automatic summarization, and more as described in this paper by McKeown et. al.
• Anyone playing with clustering algorithms needs to have a deep appreciation of the ugly duckling theorem, which says that there is no categorization without preconceptions. King and Grimmer explore this with their technique for visualizing the space of clusterings.
• Any digital journalism product which involves the audience to any degree — that should be all digital journalism products — is a piece of social software, well defined by Clay Shirky in his classic essay, “A Group Is Its Own Worst Enemy.” It’s also a “collective knowledge system” as articulated by Chris Dixon.

Measuring public knowledge
If journalism is about “informing the public” then we must consider what happens to stories after publication — this is the “last mile” problem in journalism. There is almost none of this happening in professional journalism today, aside from basic traffic analytics. The key question here is, how does journalism change ideas and action? Can we apply computers to help answer this question empirically?

• World Public Opinion’s recent survey of misinformation among American voters solves this problem in the classic way, by doing a randomly sampled opinion poll. I discuss their bleak results here.
• Blogosphere maps and other kinds of visualizations can help us understand the public information ecosystem, such as this interactive visualization of Iranian blogs. I have previously suggested using such maps as a navigation tool that might broaden our information horizons.
• UN Global Pulse is a serious attempt to create a real-time global monitoring system to detect humanitarian threats in crisis situations. They plan to do this by mining the “data exhaust” of entire societies — social media postings, online records, news reports, and whatever else they can get their hands on. Sounds like key technology for journalism.
• Vox Civitas is an ambitious social media mining tool designed for journalists. Computational linguistics, visualization, and more.

Research agenda
I know of only one work which proposes a research agenda for computational journalism.

• “Computational Journalism: A Call to Arms for Database Researchers” by Sarah Cohen et. al. raises the very intriguing possibility of building systems that automatically or semi-automatically scan databases for stories, document the rationale for believing certain facts, etc.

This paper presents a broad vision and is really a must-read. However, it deals almost exclusively with reporting, that is, finding new knowledge and making it public. I’d like to suggest that the following unsolved problems are also important:

• Tracing the source of any particular “fact” found online, and generally tracking the spread and mutation of information.
• Cheap metrics for the state of the public information ecosystem. How accurate is the web? How accurate is a particular source?
• Techniques for mapping public knowledge. What is it that people actually know and believe? How polarized is a population? What is under-reported? What is well reported but poorly appreciated?
• Information routing and timing: how can we route each story to the set of people who might be most concerned about it, or best in a position to act, at the moment when it will be most relevant to them?

This sort of attention to the health of the public information ecosystem as a whole, beyond just the traditional surfacing of new stories, seems essential to the project of making journalism work.

Live coverage

The Huffington Post, the New York Times, the Wall Street Journal, ABC, CNN, Mashable, and many others, including even Mother Jones had live web video. But you can get live video on television, so perhaps the digitally native form of the live blog is more interesting. This can include commentary from multiple reporters, reactions from social media, link round-ups, etc. The New York Times, the Boston Globe, The Wall Street Journal, CNN, MSNBC, and many others had a live blog. The Huffington Post’s effort was particularly comprehensive, continuing well into Wednesday afternoon.

Multi-format, socially-aware live coverage is now standard, and by my reckoning makes television look meagre. But the experience is not really available on tablet and mobile yet. For example, almost all of the live video feeds were in Flash and therefore unavailable on Apple devices, as CNET reports.

As far as tools, there was some use of Coveritlive, but most live blogs seemed to be using nondescript custom software.

Visualizations

Lots of visualization love this year. But visualizations take time to create, so most of them were rooted in previously available SOTU information. The Wall Street Journal did an interactive topic and keyword breakdown of Obama’s addresses to congress since 2009, which moved about an hour after Tuesday’s speech concluded.

The New York Times had a snazzy graphic comparing the topics of 75 years of SOTU addresses,  by looking at the rates of certain carefully chosen words. Rollovers for individual counts, but mostly a flat thing.

The Guardian Data Blog took a similar historical approach, with Wordles for SOTU speeches from Obama and seven other presidents back to Washington. Being the Data Blog, they also put the word frequencies for these speeches into a downloadable spreadsheet. It’s a huge image, definitely intended for big print pages.

A shout-out to my AP colleagues for all their hard work on our SOTU interactive, which included the video, a fact-checked transcript, and an animated visualization of Twitter responses before, during, and after the State of the Union.

But it’s not clear what, if anything, we can actually learn from such visualizations. In terms of solid journalism content, possibly the best visualization came not from a news organization but from Nick Diakopoulos and co. at Rutgers University. Their Vox Civitas tool does filtering, search, and visualization of over  100,000 tweets captured during the address.

I find this interface a little too complex for general audience consumption — definitely a power user’s tool. But the algorithms are second to none. For example, Vox Civitas compares tweets to the text of the speech within the previous two minutes to detect “relevance,” and the automated keyword extraction — you can see the keywords at the bottom of the interface above — is based on tf-idf and seems to choose really interesting and relevant words. The interactive graph of keyword frequency over time clearly shows the sort of information that I had hoped to reveal with the AP’s visualization.

Fact Checking

A number of organizations did real-time or near real-time fact checking, as Yahoo reports. The Sunlight Foundation used itsSunlight Live system fo real-time fact checks and commentary. This platform, incorporating live video, social media monitoring, and other components is expected to be available as an open-source web app, for the use of other news organizations, by mid-2011.

The Associated Press published a long fact check piece (also integrated into the AP interactive), ABC had their own story, and CNN took a stab at it.

But the heaviest hitter was Politifact, who had a number of fact check rulings within hours and several more by Wednesday evening. These are together in a nice summary article, but as is their custom the individual fact checks are extensively documented and linked to primary sources.

Audience engagement

Pretty much every news organization had some SUTO action on social media, though with varying degrees of aggressiveness and creativity. Some of the more interesting efforts involved solicitation of audience responses of a specific kind. NPR asked people to describe their reaction to the state of the union in three words. This was promoted aggressively on Twitter and Facebook. They also asked for political affiliation, and split out the 4000 responses into Democratic and Republican word clouds:

Apparently, Obama’s salmon joke went down well. The Wall Street Journal went live Tuesday morning with “The State of the Union is…” asking viewers to leave a one word answer. This was also promoted on Twitter. Their results were presented in the same interactive, as a popularity-sorted list.

Aside from this type of interactive, we saw lots of agressive social media engagement in general. The more social-media savvy organizations were all over this, promoting their upcoming coverage and responding to their audiences. As usual, the Huffington Post was pretty seriously tweeting the event, posting about updates to their live blog, etc. and going well into Wednesday morning. Perhaps inspired by NPR, they encouraged people to tweet their #3wordreaction to the speech. They also collected and highlighted reaction from teachers, Sarah Palin, etc.

But as an AP colleague of mine asked, engagement to what end? Getting people’s attention is great, but then how do we, as journalists, focus that attention in a way that makes people think or act?

The White House

No online media roundup of the SOTU would be complete without a discussion of the White House’s own efforts, including web and mobile app presences. Fortunately, Nieman Journalism Lab has done this for us. Here I’ll just add that the White House livestreamed a Q&A session in front of  an audience immediately after the speech, in which White House Office of Public Engagement’s Kal Penn (aka Kumar) read questions from social media. Then Obama himself did an intervew Thursday afternoon in which he answered questions submitted as videos on YouTube.

The most damning section of the report (PDF) is titled “Evidence of Misinformation Among Voters.”

The poll found strong evidence that voters were substantially misinformed on many of the issues prominent in the election campaign, including the stimulus legislation, the healthcare reform law, TARP, the state of the economy, climate change, campaign contributions by the US Chamber of Commerce and President Obama’s birthplace. In particular, voters had perceptions about the expert opinion of economists and other scientists that were quite different from actual expert opinion.

This study also found that Fox viewers were significantly more misinformed than average on many issues, which is mostly how this survey was covered in the blogosphere and mainstream news outlets. I think this Fox thing is a terrible diversion from the core problem: the American press did not succeed in informing the public. Not even right before an election, not even on the narrow set of issues that, by survey, voters cared to base their votes on.

The travesty here is that the relevant facts were instantly available from primary sources, such as the Congressional Budget Office and the Intergovernmental Panel on Climate Change. I interpret this failure in the following way: for many kinds of issues, the web makes it easy to find true information. But it doesn’t solve the problem of making people go look. That, perhaps, is a key role for modern journalism. Unfortunately, modern American journalism seems to be very bad at it. I imagine the same problem exists in the journalism of many other countries.

What the study actually says
The study compares what voters think experts believe with what those experts actually believe. This is a bit tricky, and the study isn’t saying that the experts are necessarily right, but we’ll get to that. First, some example findings:

• 68% of voters thought that “most economists” believe that the stimulus package “saved or created a few jobs” and 20% thought most economists believe that the stimulus caused job losses, whereas only 8% correctly said that most economists think it “saved or created several million jobs.” (The Congressional Budget Office estimates that the stimulus saved several millions jobs, as do 75% of economists interviewed by the Wall Street Journal.)
• 53% of voters thought that economists believe that Obama’s health care reform plan will increase the deficit, while 29% said that economists were evenly divided on this issue. Only 13% said correctly that a majority of economists think that health care reform will not increase the deficit. (The Congressional Budget Office estimates a net reduction in deficits of $143 billion over 2010-2019, and Boards of Trustees of the Medicare Fund also believe that the Affordable Care act will “postpone the exhaustion of … trust fund assets.”)
• 12% of voters thought that “most scientists believe” that climate change is not occurring, while 33% thought scientists were evenly divided on the issue. That’s 45% with an incorrect perception, as opposed to the 54% who said, correctly, that most scientists think climate change is occurring. (Aside from the IPCC reports and virtually every governmental study of the issue worldwide, an April 2010 survey of climate scientists showed that 97% believe that human-caused climate change is occurring.)

A fussy but necessary digression: all of this rests on the reliability of the WorldPublicOpinion.org survey results. The survey was conducted by Knowledge Networks, Inc. using an online response panel randomly selected from the US population. Those without internet access were apparently provided it for free. I have been unable to find any serious independent evaluation of Knowledge Networks’ methodology, but their many research papers on sample design certainly talk the talk. All of the basic sampling errors, such as self-selection and language bias (what about Hispanics?) are at least addressed on paper. The margin of error is reported as 3.9%.

So let’s take these survey results as accurate, for the moment. This means that the majority of the American public had an incorrect conception of expert opinion on the issues that they voted on. That’s a mouthful. It’s not the same as “believed false things,” and in fact asking “what do you think experts believe” deliberately dodges the tricky question of what is true. If there is some misperception of expert belief, then in the strictest terms the public is misinformed. The study addresses this point as follows:

In most cases we inquired about respondents’ views of expert opinion, as well as the respondents’ own views. While one may argue that a respondent who had a belief that is at odds with expert opinion is misinformed, in designing this study we took the position that some respondents may have had correct information about prevailing expert opinion but nonetheless came to a contrary conclusion, and thus should not be regarded as ‘misinformed.’

So this study does not say “the American public are wrong about the economy and climate change.” It says that they haven’t really looked into it. I’m all for questioning authority’s claim to truth – anyone who follows my work knows that I’m generally a fan of Wikipedia, for example — but I believe we must take lifelong study and rigorous methodology seriously. To put it another way: voting contrary to the opinions of economists may be a fine thing, but voting without any awareness of their work is just silly. Yet that seems to be exactly what happened in the last election.

The role of the press, then and now
Of course, voting is hard and stuff is complex, which is why we rely on the media to break it all down for us. The sad part is that economics and climate change are familiar ground for journalists. It’s not like the facts of these issues were not published in mainstream news outlets. For that matter, journalists were not even necessary here. Any citizen with a web browser could have found out exactly what the Affordable Care Act was predicted to do to the deficit. The Congressional Budget Office published their report and then blogged about it in plain language.

Maybe publishing the truth was never enough. Maybe journalism never actually “informed the public,” but merely created conditions where the curious could get themselves informed by diligently reading the news. But on big issues like whether a piece of national legislation will affect the deficit, we no longer need professionals to enable this kind of self-motivated discovery. The sources go direct in such cases, as the Congressional Budget Office did. And do we really expect that the social media sphere — that’s all of us — will remain silent about the next big global warming study? We’re all going to use Facebook etc. to share links to the next IPCC report when it comes out.

If the problem of having access to true information about these sorts of “votable issues” is solved by the web, what isn’t solved by the web is getting every voter to go look at least once. That might be a job for informed professionals at the helm of big media channels. This is a big responsibility for a news organization to try to take, but I don’t see how it’s anything but the corollary to the responsibility to only publish true information. Presumably some of that information is important enough to know, so consumers would probably appreciate the idea that your mission is to ensure they are informed.

I suspect that paper-based habits are holding journalism back here. There is a deeply ingrained newsroom emphasis on reporting only what’s “new.” A budget report only gets to be news once, even if what it says is relevant for years. But there are no “editions” online; the same headline can float on the hot topics list for as long as it’s relevant. There is even more reason to keep directing attention to an issue if people are actively discussing it, if it is greatly polarized, or if there’s a lot of spin around it (see: the rise of fact-check journalism). In any case, journalists have long been good at keeping an issue in the news, by advancing the story daily in one way or another. But first they have to know what the public doesn’t know.

So the burning question that the World Public Opinion study leaves me with is just this: why wasn’t it a news organization that commissioned this survey?

See also: Does journalism work?

Journalism, capital J, is supposed to be about ideals such as “democracy” and “the public interest.” It’s probably important to be an informed voter, but this is a very shallow theory of why journalism is desirable. Most of what we see around us isn’t built on votes. It’s built on people imagining that some part of the world should be some other way, and then doing what it takes to accomplish that. Democracy is fine, but a real civic culture is far more participatory and empowering than elections. This requires not just information, but information tools.

Newspaper stories online and streaming video on a tablet are not those tools. They are transplantations of what was possible with paper and television. Much more is now possible, and I’m going to try to sketch the outlines of how newsroom products might better support the people who are actually changing the world.

What’s a journalism “product”?

This is an essay about product design, so I want to be clear on what I mean by a journalism “product.” Since journalists don’t make tangible objects, the product is defined by the user’s experience. It’s whatever the user interaction with the news is. It’s picking up the paper at breakfast, or watching CNN in bed, or waiting for your mobile app to update the headlines on the bus. And yes, the product includes the stories delivered by the medium, but those stories alone are not the product; they never were. The stories were packaged into a newspaper or a television show, and that was the product. Or more precisely, the newspaper and the television show as the user chose to use it was the product.

Much of the ongoing future-of-journalism discussion focusses on how reporting needs to change, and rightly so. But that analysis stops short of the user, and how journalism is actually used — or could be used.

Digital news product design has so far mostly been about emulation of previous media. Newspaper web sites and apps look like newspapers. “Multimedia” journalism has mostly been about clicking somewhere to get slideshows and videos. This is a little like the dawn of TV news, when anchors read wire copy on air. Digital media gives us an explosion of product design possibilities, but the envisioned interaction modes have so far stayed mostly the same.

This is not to say that the stories themselves don’t need to change. In fact, I think they do. But the question can’t be “how can we make better stories?” It must be “who are our users, what would we like to help them to do, and how can we build a system that helps them with that?”

Maybe the product has to include advertising too, and maybe it must be subsidized with celebrity gossip and movie listings. There are clearly business considerations in defining journalistic products, and that’s fine, but I’m going to focus on the user experience here. Lots of other people are already talking about the business of journalism. I’m trying to make something that actually fills a need in people’s lives. If you can do that you’ll have an audience, and then you can advertise to them or sell them subscriptions, or syndicate the product, or whatever.

The first thing I ask of an improved product is this: I want people to use it. Or rather, I want people to want to use it.

Is the news boring?

By boring I mean unengaging. Not something you want to spend a lot of time with. As Joshua Benton of the Nieman Journalism Lab put it,

You never hear from people “Man, I just got lost on that news site!” We don’t create experiences that people just want to live in for a while.

He was referring to the following fact: Americans apparently spend 12 minutes a month on the average news site, versus seven hours per month on Facebook. (I’ll use American numbers as illustrative, because they’re well studied. Please let me know of data for other countries!)

It’s not that people are paying less attention to the news than they used to. American spend about 70 minutes a day with all news media, the same as in 1996. (Most of that is television news, but online consumption is climbing.) Meanwhile, total consumption of media is at an all time high. This discrepancy in growth means that people aren’t choosing to spend their increasingly connected time learning about the world — or at least they’re not learning about it through professional journalism.

I think that this is because existing journalism formats are not very good at engaging curiosity.

I’m not talking about making the writing “sharper”, adding “multimedia”, or doing better page layout. Those might be good ideas, but it’s all rearranging the furniture. There’s no fundamental change in such things. When editors give smug interviews about their publication’s “fresh new style” I want to throw things. It’s still exactly the same model of interacting with the user. There are better ways.

Design for curiosity

I live surrounded by infophiles, and for almost all of them Wikipedia is a better resource than a news site when they want to learn about the world. People spend hours roaming Wikipedia; they don’t spend hours on bbc.co.uk or cnn.com or nytimes.com or news.yahoo.com (which actualy has a far bigger audience than any traditional news outlet.) Wikipedia also tends to take the top spot in Google results, which means that more people link to it than they do to any news site.

Why is this? If professional news products are supposed to be such a vital resource, why are users overwhelmingly choosing to satisfy their curiosity elsewhere?

I think the answers to this are starting to be understood. Standard news coverage is written as a series of incremental updates, which are useless if you’re not already following the story closely. When I returned to coverage of the oil spill after not checking on it for a couple of weeks, Wikipedia was far, far better at bringing me up to date on the story. If I’d gone to CNN I would have been forced to wade through a series of daily updates to learn what I wanted to know. This has become known as the “context” problem within the future-of-journalism community, and there’s no better introduction to it than Matt Thompson’s “An Antidote for Web Overload.”

The professional news media also have a serious problem with linking, or rather, not linking. Linking is vital for creating immersive experiences online. Links create the web, the greatest time waster ever invented. They’re also neccesary for any site that wishes to be indispensable. I don’t want the product with the best content overall, I want the product that is going to serve me up the best content every single time, regardless of whether or not it was created in-house. That means links. (And content syndication, but no walled garden will ever match the wild richness of the whole web.)

Links are also vital for transparency and depth; they provide the option of more serious investigation. The uses of links in journalism, and their relative paucity in professional work, is a topic I covered in great detail in a three part series for the Nieman Journalism Lab this summer, and I also wrote about the use of links for deep storytelling here. But to make it short: linking is not yet part of professional journalism culture, and this creates a serious problem with the product.

There are many other features that afford the satisfaction of curiosity. Take the humble “search” box. Almost every news site has one, and search is an obvious way for a user to answer their question. But news web sites almost always implement search badly, and many news apps don’t even have a search function. Or, you can only search content from last few days or within the current “issue.” I don’t care about the metaphor of “issues” when I have a specific desire to learn something.

And then the river of data stemming from search logs is poorly analyzed. There is an ongoing debate about exactly how much news organizations should respond to user demand. If “Paris Hilton” is the number one search, I don’t think that the newsroom should make Paris Hilton stories their number one priority, but ignoring what users want is folly. And it’s no way to engage my curiosity, which is about what I think, not what the editor thinks.

Don’t fear fragmentation

Which leads us to another deep problem with existing journalism products: they’re not designed to be personal.

Perhaps this stems from the classic “we’ll tell them what they need to know” mindset among editors. That makes sense for a paper product, where everybody reads exactly the same copy, and you can actually “finish” consuming the content when you run out of pages to read. It doesn’t make sense when pages are effectively infinite, and there’s no obvious reason that my reading should overlap with yours. Grizzled hacks love the idea of everyone talking about the same set of stories, just like the good old days, but I don’t believe that, today, it is a reasonable thing to expect or want.

NYU journalism profession Jay Rosen recently introduced me to a 20th century social critic named Raymond Williams. “There are no masses, “ Williams wrote in 1958, “there are only ways of seeing people as masses.” Lofty discussions of journalism use words like “public” and “citizen,” but of course those are ideas. There is no homogenous audience. And at last it is possible for our media to reflect this truth, because the internet is not a broadcast medium. A newspaper or a TV report is the same experience for everyone, while my usage of a web site or an app can be extremely personal.

Then we have the problem of information overload. One person can only track so many stories. If everyone follows the same few stories, lots of important things are going to be ignored. (Which is exactly what’s happening now, according to internet scholar Ethan Zuckerman.) Delivering the same information to everyone and expecting that everyone engage it equivalently is not only an insult to diversity, it ignores that fact that our civilization is built on specialization. Different people have different capabilities, positions, and passions, and so they’re going to need different news agendas. Empathetic journalists have always been aware of this, but it wasn’t previously possible to target individual stories to specific people.

This targeting is something that users could do for themselves to a large extent, given the right interface. Today, the personalization features of almost every digital news product amount to 1) showing me stories that happen in my zip code and 2) letting me pick from a small set of coarsely defined “sections.” Why can’t I subscribe to updates on particular stories? Why can’t I set up alerts for particular terms? Why can’t I tell my news app “no more updates on Lindsay Lohan, ever”? Etc.

Who needs to know?

If we’re going to try to deliver specific stories to specific people, then who should we target? First of all: anyone who wants to know. The broadest possible access is important, and happily, the internet has been very good at extending access.

Beyond that, I go back to the idea that journalism should be useful by those who are acting to change and build our societies. Then the answer is “whoever is going to do something about it.” The product should serve the people who choose to act.

Some people will have shaping society as part of their job description, such as teachers and civil servants. Other’s won’t, and this is truly a great era to be an interested amateur. It’s not that every individual is a motivated genius just waiting for the right call to action. Rather, let’s say that there is tremendous knowledge and capability scattered throughout society, untapped. Some people are highly trained specialists with spare weekends. Other are merely informed and interested.  Some problems call for unskilled mass participation, but many more call for the dedication of a small number of the right sort of people.

My favorite example of this is the The Guardian’s successful attempt to find someone among their audience who could untangle the mystery of Tony Blair’s tax returns. Eventually, some crusading geek of an accountant stepped forward with the solution (and bravo to you, sir.)

In fact, we know that most people won’t work on anything at all. This is the nut of the 90-9-1 rule which seems to hold across many different types of online social activities: 90% of people are just audience, 9% are involved in some way, and only 1% are the real creators. The numbers vary somewhat from platform to platform, but the upshot is always that only a very small number of people do the core work. There’s no reason to believe that offline social initiatives — everything from campaigning for gay rights to  getting potholes repaired – would typically attract a much broader base of core agents. And this is fine. This is normal, and nothing to be upset about. One percent of a population is still a huge pool of talent and labor.

In this framework, the purpose of journalism is to deliver each story to the right 1%, at the point when they need it. Saying that most people won’t read a story about Madagascar doesn’t get us very far; that’s expected, and that’s the only way it can be in an era of spectacular information overload.

I don’t know whose job it is to facilitate the creation and nurturing of communities around issues; maybe it’s fine to let Facebook have this role. What I do know is that journalism needs to concern itself explicitly with figuring out who its audience is — for each story, down to the level of individual people and groups. Where in the world are those 1% who have something to say or do about the coup in Madagascar, and how do we connect to them, and connect them to each other?

This probably requires that journalists listen a lot better to what’s already happening out there on the tubes. As Felix Salmon of Reuters puts it, we need to teach journalists to read.

Journalism designed for agency

I come from a culture of makers; my personal life and my chosen communities are steeped in the ethic of hackers, entrepreneurs, crafters and artists. All of these activities are the expression of a participatory instinct, an instinct that extends to trying to shape the society we live in. I want information systems that facilitate self-selected civic action and social entrepreneurship in all its forms. If this is the goal, then journalism needs a better understanding of how its products could actually be used to effect change.

News can no longer be (only) about the mass update. Stories need to be targeted to those who might be able to improve the situation. And journalism’s products — which are more than its stories — must be designed to facilitate this.

News needs to be built to engage curiosity about the world and the problems in it — and their solutions. People need to get lost in the news like they now get lost in Wikipedia and Facebook. There must be comprehensive stories that get the interested but uninformed up to speed quickly. Search and navigation must be improved to the point where satisfaction of curiosity is so easy it becomes a reflex. Destination news sites need to be more extensively hyperlinked than almost anything else (and not just insincere internal links for SEO, but links that are actually useful for the user.) The news experience needs to become intensely personal. It must be easy for users to find and follow exactly their interests, no matter how arcane. Journalists need to get proficient at finding and engaging the audience for each story.

And all of this has to work across all modes of delivery, so it’s always with us. Marketers understand this; it’s amazing to me that the news industry has been so slow to catch on to multi-modal engagement.

It sounds like a tall order, but there’s nothing here that requires exotic technology. Just real product design, in pursuit of concrete journalistic goals.

(thanks to @chanders for feedback on an early draft of this post)

(Click for larger.) As opposed to most of the other “blocked site” screens, you don’t actually have to be in country to see this, just go to http://www.censor.qa/.

Next up, Bahrain:

Lest the Westerners in the audience get the impression that blocking internet access is all about silly little theocracies in the desert, note that Australia just passed an internet censorship law. The blacklist is secret. Stay tuned for “What Internet Censorship Looks Like in Australia”!

I got three immediate answers:

“The West.”

“Japan.”

“Separatists.” (E.g. Tibetans, Uighurs.)

There was instant consensus on this list, among the PRC students. Good to know.

The president did not lie. All of the proposed health care reform bills contain language excluding those residing illegally in the US from government-subsidized coverage. This single-sentence fact check was entirely absent from 50 of the 70 articles mentioning “wilson” and “lie” on the New York Times and Washington Post websites as of Monday night. Of the 20 which discussed actual policy, only nine articles mentioned it in the first two paragraphs. (Spreadsheet here.)

Wilson’s outburst will be forgotten long after millions of Americans are insured — or not — under Obama’s plan. It’s just noise and heat. Yet some of the most reputable newspapers in the world have lead with it for the last five days. In fact, the press has in some cases actively dodged the underlying issue. Consider this exchange from an online Q&A session with Dana Milbank of the Washington Post:

Cincinnati: Are you saying the President wasn’t lying when he said illegal immigrants won’t be covered? Why not look at the House bill and tell us whether or not it allows illegals to be covered? The Congressional Research service issued a report last week saying there was NOTHING in the House bill that excludes illegals from receiving government-run health care. In other words, be a REPORTER instead of a hack for Barack.

Dana Milbank:  Actually I wasn’t addressing the factual nature of Obama’s speech. The issue wasn’t that Wilson thought the president wasn’t telling the truth; part of the presidential job description calls for expertise in truth shading. The issue was shouting “you lie!” at the president on the House floor during an address to a joint session of Congress.

(For the record, the CRS report in question notes that HR 3200 says “Nothing in this subtitle shall allow Federal payments for affordability credits on behalf of individuals who are not lawfully present in the United States.” Which has, oddly, been spun as meaning that illegals would be subsidized!)

It should be no surprise that there is actually substance to the question of coverage for illegal immigrants. Only nine of the 70 pieces get into it: yes, a few undocumented workers could end up getting subsidized health care. No, it’s not worth taxpayer money to add an enforcement mechanism.

But even this is one level removed, and only one article grappled with the fundamental question: would it really be so bad if the poorest workers in America got a break? In fact we might even owe it to them. On average, migrant labor is thought to be a small net gain to the American economy.

I get that Wilson’s little moment is a great story, right up there with the guy who threw a shoe at Bush (who was imprisoned for his prank, with far less coverage.) And I do understand the logic of a populist press as the paper ship sinks. What cannot be excused is the omission of any mention of the substantive content of the debate from the majority of coverage — 50 out of 70 articles said nothing at all about anything that will last.

We are reporting on court theatrics while the citizens starve.

Marc Lynch at Foreign Policy writes a classic post about rapper The Game’s recent attacks on reigning power Jay-Z, and uses the spat as an allegory for international relations and the options open for an American hegemonic power.

Nobody, but nobody, in the hip hop world has his combination of hard power and soft power. The changes in Jay-Z’s approach over the years suggest that he recognizes the realist and liberal logic… but is sorely tempted by the neo-conservative impulse. Back when he was younger, Jay-Z was a merciless, ruthless killer in the “beefs” which define hip hop politics.  He never would have gotten to the top without that.  But since then he’s changed his style and has instead largely chosen to stand above the fray.   As Jay-Z got older and more powerful, the marginal benefits of such battles declined and the costs increased even as the number of would-be rivals escalated.  Just as the U.S. attracts resentment and rhetorical anti-Americanism simply by virtue of being on top, so did Jay-Z attract a disproportionate number of attackers.   “I got beefs with like a hundred children” he bragged/complained on one track.

Some of the responses in the comment thread are even better:

If perhaps Switzerland had once been a British colony which rebuilt itself after World War II as the Japan-like embodiment of a modern technocracy…then maybe Jay-Z could be thought of as that nation-state. And if the U.S. were a rapper, I’m sad to say…we’d probably be 50 Cent. Clumsy commercialism passed off as art, unmerited bellicosity, unmatched market penetration, and the diminishment of formerly venerated (and historically better pedigreed) entities, with a commercially viable pile of sex-sex-sex on the side.

We WISH this country was like Jay-Z….

As far as I’m concerned, Marc just made his career with this track. If this doesn’t get hip-hop into Ivy League faculty parties and ghetto kids spitting geopolitics, I don’t know what will. (Via Abu Muqawama.)

The background: Attorney Rodrigo Rosenberg was shot while riding his bicycle on May 10th, just a few days after recording a video message which begins,

If you are watching this message, it is because I was assassinated by President Álvaro Colom.

The video implicates not only the president but the major state-owned bank, and indeed much of the current government, and there were mass protests in the capital city. Xeni has been covering the story from Guatemala since the 20th, and I can only commend her for actually being there. However, her coverage has focussed on the role of the internet in these protests.

Google is not reality and Twitter is not reality in exactly the same way that television is not reality. Part of the reason that Middle-Eastern peasants have such a warped view of America is that they too watch Desperate Housewives (via satellite or bootleg VCD), but never get the chance to actually meet some Americans. To them, all American women are blonde and slutty. There’s no reason to believe that we’re not getting a similarly warped view of other cultures when we watch their internet.

For it is something else entirely to be walking the streets of a foreign country. It’s a different world; the language is different and the food is different and the way things get done are different. We can fire up our web browsers and speculate about Facebook-organized protests, but it means nothing without the context. Maybe people in the Guatemalan cafes are angry, maybe they are apathetic; or maybe talking about politics over coffee is a luxury that the desperately poor rural population cannot afford, along with internet access. The only way to know is to go there.

Therefore, Kudos to Xeni for understanding the value of on-the-ground journalism, for being there, and for putting in so much time trying to learn something about people in another country. Consequently I am a little surprised that she would write,

Rosenberg’s video was handed out on DVDs at his funeral. The footage spread within days to YouTube and other video networks. Soon, it was the focal point of chatter among mostly young Guatemalans (who are more well-off than Guatemala’s extremely poor majority) on social sites like Twitter, Facebook, and Hi5. Remixes of the video soon appeared online, along with subtitled versions and amateur op-ed responses to the claims therein.

Those same social networks also played a role in organizing massive demonstrations in the country’s capital, Guatemala City. Crowds one weekend were estimated to be between 30,000 and 50,000. Newspapers in Guatemala credited social networks such as Facebook and Hi5 with “summoning” the petition signers.

The implication of this — and of the headline “The Twitter Revolution” — is that online tools played a crucial role in the spread of information and the organization of protests. But I don’t think we actually know this; I don’t think we actually can know it just from watching Twitter and Facebook and counting the number of webcasts. It’s exciting to talk about the role of technology in social justice, but these are just the most externally visible pieces of a huge and complex phenomenon.

So what role did “new media” actually play in spreading and coordinating organized dissent? Did anyone survey the protesters and ask them how they heard about the protest?

I can just as easily imagine that Twitter and Facebook and all the rest played only a relatively minor role in the massive response to Rosenberg’s death. Communication networks existed long before technology, in the form of dense and fast-responding social networks. When my friend had a motorcycle to sell in a small town in India, he walked into a dealership. The dealer didn’t buy his bike and my friend walked away without giving any contact information, but four hours later a pair of Tamil men knocked on his hotel room door with an offer of 15,000 rupees cash. In India, communication moves with astonishing speed along the networks of big extended families, business partnerships, chatter at the chai stand, and other channels I was never privy to.

And so we come to someone handing out DVDs of Rosenberg’s last statement at his funeral. The DVDs were played on existing, ubiquitous, cheap technology (DVD players now cost under $20 worldwide). They were doubtless copied and probably re-copied onto VCDs which can be duplicated on any dirt-cheap relic of a computer, and endlessly passed hand to hand. Meanwhile, unlike computers and internet access, mobile phones really are a ubiquitous technology, and surely good old-fashioned telephone gossip played a huge role.

It would have been weird if the video hadn’t eventually been posted online and the topic had never made it to Twitter. But just because something was online doesn’t mean that it had any effect. “Online” is just the part of a culture’s psyche that is easiest to measure,  and it’s also exciting to report on if you’re an idealistic technologist (like me.) And it’s the preferred method of young, well-off Guatemalans who are politically motivated and rich enough to spend endless hours online in a country where bandwidth is very expensive, in relative terms. These are precisely the people who a tech-savvy foreigner like Xeni would be spending the most time with.

This problem of understanding is not unique to Guatemala, of course. One of my favorite pieces of research is the study of Iranian bloggers that came out of the Berkman Center for Internet and Society which I have previously commented on here. Not only did this work dispel some dearly-held new media myths (e.g. “the majority of Iranian bloggers are politically liberal,” which is just not true) but it raised some really tricky questions about the relationship between a society and its online footprint. Who, exactly, are these people writing blogs?

So, Xeni, I have some questions about Guatemala’s ”Twitter revolution.” You were there, so perhaps you can shed some light on them:

• What fraction of the Guatemalan population has internet access?
• How many Guatemalan Twitter users are there?
• What is the demographic of each of these groups? What is known about the political leanings of these demographics?
• How many users joined Facebook groups concerning the protests? How many protestors were there? How does this ratio compare with protests organized online in developed countries?
• Was/is the Rosenberg video widely copied and circulated on DVD/VCD? Can you buy it at street level from the usual sources for pirated videos?
• What is know about SMS usage in these protests, a technology which is far more widely deployed than Twitter?
• Finally, did you get the chance to ask random protestors how they heard about the protest?

If we truly believe in the potential for new media in social change — and I certainly do — then we have to be ruthlessly honest about the cause and effect relationships involved. Yes, mass protests really are organized online in our rich and digital corner of the world, but that doesn’t mean that anyone else does it the same way. If Guatemalans might mistakenly think that all Americans act just like they do on TV, we’re in danger of believing that all Guatemalans act just like they do on the internet.

UPDATE: And it turns out that a key piece of context was missed by the twitter stream and related commentary: the counter-protests for Colom that took place. These were reportedly of the same magnitude as the anti-Colom demomstrations, but they involved slum-dwellers and the rural poor, who don’t tweet.