Just came across a couple of great videos on the future of content and journalism from the Web 2.0 Summit 2009. The first is titled The Future of Content, and can be viewed below:
The second is titled Whither Journalism, and is shown below:
Over a year old now. I think the debate has evolved a bit since these panels, but still quite relevant.
An interesting look behind the scenes at Citizen Journalism startup AllVoices – from PBS Mediashift:
There are some interesting observations and comments in this video that shed insight into the core competencies of the future news organization. From the first part of the video, a few observations:
- Low cost structure – The company employees relatively few staff, where each person where a lot of different hats – the prototypical startup
- Community Management – Strong emphasis on Community Management, and the role of the Community Manager
- Copyright – A need to manage copyright violations – for both professional and user-generated content – which AllVoices manages by NLP algorithms (recognizing sequences of 5 identical terms)
- Marketing – The Community has become the evangelist for AllVoices, which has helped AllVoices tremendously in creating buzz. People promote their content on Social Networks and other sites. AllVocies depends on their community to do their marketing for them … it’s all about the Community.
The second part of the video (starting at approx 5:29) is an interview with AllVoices’ CEO Amra Tareen and VP Social Media, Erik Sundelof. Some insightful quotes in this segment. Here’s a few:
Amra Tareen: So when AllVoices started, what we wanted to do was create a place where people could report regardless of where they are, from any device – cell phone, computer, using MMS, SMS, e-mail, or just going to the website.
When they send us something, what we want to do is geolocate – where exactly is it coming from? In AllVoices, we can detect locations down to any place greater than 500 people … So any city in the world we can detect where the message or report is coming from.
And then we try to geolocate, based on the IP address, based on the cell phone #, based on any tags the user adds to their text.
Amra Tareen: Now there are two types of content that come into AllVoices. One is “user reported”, the other is what our system aggregates from news sources and news feeds all around the world.
So, first, we geolocate, we categorize – whether you’re talking about Politics, Conflict and Tragedy, Sports, Entertainment. Then what we do is break it down, do contextual analysis to “bag of worlds“.
Then based on those bag of words, … we want to showcase the user report, as well as create context around that report by aggregating related information.
… Since we already break it down into keywords, we know what the tags are for that user report. But we let the user add the tags themselves. Because sometimes the machines are not always as accurate as the user is. And that’s what we’ve learned – AllVoices is based on Machine Learning and the Community, and the Community always corrects the Machine Learning.
So some interesting stuff here. Once again (that is, I have strongly advocated this position in previous posts), the future of Journalism will be significantly about a balance between Machine Learning and the Community … and the many, many technologies that support the interface between the two.
Let’s see what Erik Sundelof, AllVoices’ VP Social Media, has to say:
Erik Sundelof: If you are doing cell phone reporting or “in the field” reporting, you have to bring in the context, and [show people that context].
At All Voices, we try to bring in all the different content and media types … By doing this, you will also be able to determine how credible a particular report is.
If user content is coming in very short, very opinionated peices – which I really think is what Citizen Journalism should be about, bringing in the more emotional side, and telling what is really going on on the ground – that doesn’t mean that it’s fact checked. But you can’t fact check the complete flow of information in free-form. So you have to apply technology on top of it.
How does AllVoices’ system deal with “hoaxes” reported by the community?
Erik Sundelof: The way we are attacking the “hoaxes” problem is through “credibility”. A hoax is just another story. We’re still going to apply the same methodology, because everything is a computerized [algorithim]. So this means if the hoax comes in, and no one is talking about it, then it will just drop off the system. It will still have a page, because it’s a free publishing platform. So you will get your page, but it won’t show in the landing pages because no one will view it.
Amra Tareen: And each page has a credibility rating. So every report in AllVoice has a 5-bar credibility rating. So based on the activity level, based on similirity of content we find on AllVoices and off of AllVoices, I think the likelihood of a hoax being report is small, compared to some person individually fact-checking, and trying to figure it out.
Interesting perspectives – again, particular around the intersection of machine learning and the crowd-sourced journalism and content.
Fascinating. So first I just came across the website Newspaper Death Watch, and I must say I find its perspective fascinating. Secondly, while on the site, I came across an interview with two documentary filmmakers – Adam Chadwick and Bill Loerch – who are producing a documentary called Fit to Print, about the decline of the Newspaper industry in the U.S., I believe with a specific focus on the New York Times. Anyway, here’s the clip:
Interesting times, and yet a time that arouses compassion also.
In a recent post, I highlighted a presentation delivered by Leonard Brody on Change and Entrepreneuralism. Here’s another presentation given by Brody in January 2009 in Qatar on how Journalism and News Media are changing in a 24×7 connected world:
He’s a great speaker I might add.
There is certainly an enormous amount of energy being applied to “reinventing Journalism” – both the trade and the business – for the digital age.
Quoting Winer in his blog post from January 14th:
I have the same feeling about journalism today that I had about computer science in the 1970s. … Today, 2010, is Year Zero for journalism the way 1970 was the dawn of modern computer science.
He may be right.
Here’s the same announcement from Jay Rosen.
Of course, this isn’t the first time Rosen and Winer have collaborated. Check out their weekly podcast Rebooting the News.
A nice summary from Gina Chen of Marissa Mayer’s – who is Google’s VP of Search Product and User Experience – testimony to a U.S. Senate Subcomitte on the future of journalism back in May 2009. Here it is: Google’s advice to newspapers.
Nothing earth-shattering here, just another reminder of how profoundly the news media industry must, and will, change in the near future.
As society reexamines the roles of Journalists and Media companies, here’s a nice clip from Pointer’s Sense Making project from March 2009:
Thought I’d muse today about a topic I’m going to call Algorithmic Journalism. I’ve noticed a fair bit of discussion lately on the use of algorithms (typically machine-learning algorithms) to make sense of, understand the relevance of, aggregate, and distribute news.
First off, the use of machine-learning algorithms and collective intelligence to determine relevance of search and content are very common place today. They form the basis of Google’s search algorithms, and are heavily used by Amazon, Netflix, etc. However, machine-learning in Newsrooms is another matter. And it’s the discussion of machine learning in the context of the News Media business whose waves are starting to wash up against the shorelines of my personal information space (i.e. Twitter and the real-time Web!)
Here’s some of the articles/blog posts in the past few months that speak to this topic:
- Content farms v. curating farmers – Jeff Jarvis, December 2009
- A Speculative Post on the Idea of Algorithmic Authority – Clay Shirky, November 2009
- The rise of machine-written journalism – Wired Mag, December 2009
- The End Of Hand Crafted Content – TechCrunch, December 2009
- Google’s vision of the future of journalism – The Guardian, October 2009
- The Answer Factory: Demand Media and the Fast, Disposable, and Profitable as Hell Media Model – Wired Mag, October 2009
Note these articles were all written in the past few months. So the topic appears to be only recently breaking into the broader consciousness of the Journalism community.
I’d also point out that the evolution of Algorithimic Journalism is highly dependent on Semantic Web technologies. So look for the influence of the Semantic Web to continue to penetrate the Journalism industry.
Anyway, a topic to keep an eye on in 2010.