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Peace, Conflict, and Data

A talk I gave at the IPSI Bologna Symposium on conflict resolution. Slides here.

We might be able to do better at conflict resolution — making peace in violent conflicts — with the help of good data analysis. There have long been data sets about war and violent conflict at the state level, but we now have much more.

There are now extraordinarily detailed, open-source event data streams that can be used for violence prediction. Conflict “microdata” from social media and communications records can be used to visualize the divisions in society. I also suggest a long term program of conflict data collection to learn, over many cases, what works in conflict resolution and what doesn’t.

We’re really just at the beginning of all of this. There are huge issues around data collection, interpretation, privacy, security, and politics. But the potential is too great to ignore.

Update: two excellent resources have come to my attention in the days since I gave this talk (which is, of course, part of why I give talks.)

First, see the International Peace Institute’s paper on Big Data for Conflict Prevention. This paper was co-authored by Patrick Meier, who has been deeply involved in the crisis mapping work I mentioned in my talk.

But even more awesome, Erica Chenoweth has done exactly the sort of data-driven case-control study I was contemplating in my talk, and shown that non-violent political resistance succeeds twice as often as armed resistance. Her data set, the Nonviolent and Violent Campaigns and Outcomes (NAVCO) Data Project, also shows that non-violence is much more likely to lead to good democracies five years later, and that a movement that can recruit 10% of the population is almost guaranteed to succeed.

I highly recommend her talk.

What should the digital public sphere do?

Earlier this year, I discovered there wasn’t really a name for the thing I wanted to talk about. I wanted a word or phrase that includes journalism, social media, search engines, libraries, Wikipedia, and parts of academia, the idea of all these things as a system for knowledge and communication. But there is no such word. Nonetheless, this is an essay asking what all this stuff should do together.

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.

 

A computational journalism reading list

[Last updated: 18 April 2011 — added statistical NLP book link]

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.

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.

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.

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.

The state of The State of the Union coverage, online

The state of the union is a big pre-planned event, so it’s a great place to showcase new approaches and techniques. What do news digital news organizations do when they go all out? Here’s my roundup of online coverage Tuesday night.

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.

By the numbers, American journalism failed to inform voters

A recent study by World Public Opinion.org shows that the majority of the American population believed false things about basic national issues, right before the 2010 mid-term elections. I don’t know how to interpret this as anything other than a catastrophic failure of American journalism, in its most fundamental, clichéd, “inform the public” role.

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?

Designing journalism to be used

There are lots of reasons people might want to follow the news, but to me, journalism’s core mission is to facilitate agency. I don’t think current news products are very good at this.

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”?

Continue reading Designing journalism to be used

What Internet Censorship Looks Like in Qatar, Bahrain

I am collecting “censored!” screens from different countries. Thanks to the sleuthing of Jacob Appelbaum, I’ve got two more for you. When you’re not allowed to see something online in Qatar, you get redirected to this site:

QatarCensored

(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:

Bahrain-filter

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”!

Know Your Enemy

In America, the enemy is Terrorism. It used to be the Russians, or more generically Communists. We discussed the history of this concept in class today. And then I asked: In the state-controlled Chinese media, who is the enemy today?

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.

American Press Covers Debate, Not Health Care

Representative Joe Wilson yelled “you lie!” at the president, and the papers loved it. Unfortunately, by a count of more than three to one, the major media articles covering the event did not bother to comment on the substance of issue of that provoked Wilson’s outburst: whether or not illegal immigrants would be provided health care under proposed reforms. There is no health care debate in the mainstream American press. There is only political drama.

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.

Better Foreign Policy Through Hip-Hop

jay-z

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.)