Five Tech Ideas for Explanatory Journalism
At the Center for Civic Media and the Berkman Center for Internet and Society, Nathan designs and researches civic technologies for cooperation across diversity. At the Berkman Center, he applies data analysis and design to the topics of peer-based social technologies, civic engagement, journalism, gender diversity, and creative learning.
Nathan's current projects include Open Gender Tracker, Thanks.fm, and NewsPad. A full project list is at natematias.com.
Nathan regularly liveblogs talks and events. He also publishes data journalism with the Guardian Datablog and PBS IdeaLab. He also facilitates #1book140, The Atlantic's Twitter book club, and frequently hosts live Twitter Q&As with prominent writers. He coordinated the Media Lab Festival of Learning in 2012 and 2013.
Before MIT, Nathan completed an MA in English literature at the University of Cambridge, where he was a Davies Jackson scholar. In earlier years, he was Riddick Scholar and Hugh Cannon Memorial Scholar at the American Institute of Parliamentarians. He won the Ted Nelson award at ACM Hypertext 2005 with a work of tangible scholarly hypermedia. He was made a fellow of the Royal Society for the Arts, Sciences, and Manufacturing in 2013 and was an intern at Microsoft Research Fuse Labs in the summer of 2013.
Five Tech Ideas for Explanatory Journalism
How can technology help journalists make sense of complex issues and explain them to the public in a clear, understandable manner?
Last year, Jay Rosen's journalism students spent an entire semester researching and making explanations in partnership with ProPublica, a non-profit newsroom which focuses on investigative journalism. The class did amazing work to highlight notable examples and develop their own explainers. One of my favourite examples is this project from 2011, where students redesigned the same ProPublica background article as a video, a podcast, and an FAQ.
NYU's Explainer class focused on two things: presentation and conversation. They talked to cognitive psychologists like George Lakoff to learn how audiences take in what we read. They highlighted numerous presentation examples-- videos, timelines, infographics, mini-sites, aggregators, podcasts, interactive guides, flowcharts, and even a picture book by Google! The class at NYU also pointed out that explaining is often a conversation. In their journalist's guide to developing FAQs, the class suggests techniques for discovering what people need to know. I loved their advice on listening to readers.
Where Can We Innovate?
This term, I'm taking the Participatory News class from the point of view of a technology designer who wants to build tools to support great journalism. Instead of going deep on a particular story, I kept my eyes open for parts of the process which technology could improve. Here are my top tech recommendations for supporting beter explainers:
Jay points out in several places that it's okay and even desirable to have a non-expert reporter create explainers. When learning how to explain something, our initial ignorance helps us appreciate where our audiences are coming from. This approach still puts professionals in the role of sorting and presenting explanations.
I think we should take inspiration from Wikipedia to develop strategies for peer production of explanatory journalism, especially for issues that journalists can't or won't cover. Online communities like Metafilter have proven their ability to cooperate on investigations on occasion. How can we extend that to explanations? My muses here would be Instructables and CommonCraft, online communities of people who share video instructions and explanations.
Building online communities is hard. Instead of developing an "explainer" community, I would build a toolkit which existing communities can use when they feel the need to investigate and explain an issue.
Many of the explainers took on a narrative form. The Giant Pool of Money succeeded because This American Life found the right cast of characters to illustrate a complex issue. But finding the right people is really hard, especially if you're not a mainstream media organisation. Source databases such as The Public Insight Network can help, but it's a closed system unavailable to bloggers and ordinary people. Social Media networks through groups like Global Voices get us part of the way, but only as far as people who might know the people we're looking for.
I'm not sure the crowd can help here. In many cases, the people you want to interview might not be outspoken online. Instead, I would build tools which support a research process carried out by individuals or small teams. The tool would offer encouragement and ideas for following the trail from an effect to an individual.
We could support one workflow in particular. Given a set of articles which are already about a topic, we could automatically extract the names of the organisations and individuals who are quoted and referred to, creating a quick map of the issue in the media. A canny storyteller might be able to spot gaps in the story or simply remix existing material into an explainer.
Writing a good explainer requires three kinds of information organising: the micro-model you use to conduct an interview; the evolving model you use as a journalist to understand the issue; and the model you present to your readers.
The most widely used writing tools are terrible at helping people organise and understand their information. I have written elsewhere about my use of tools like Tinderbox to organise research around a complex issue. I think we need more of that kind of software.
All storytelling on computers is in its early stages; we haven't agreed on very many common literary forms. Beyond the FAQ, the Timeline, and the illustrated lecture, most explainers require a custom rhetorical form. That's bad for news organisations, who prefer to put deadlines on a project.
That's why I love The Explainer Awards that Jay Rosen and his students held. Awards are a great way to create norms and highlight innovation-- they have been an effective model as far back as 5th century Athens. But we need to take this further. An effective awards programme would bring together finalists in each category to discuss common challenges and build technologies to solve those problems.
Why not re-imagine explaining as a social movement rather than content production? Some of the best explaining comes from a two-way conversation, not a piece of content. We could start a service called Meet the News, a geolocated service which invites anyone to have coffee with someone affected by a news story. Participants could pay for the coffee and might be expected to contribute back to the community with a few paragraphs about the conversation, just like couchsurfing reviews.