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March 29 2010

17:47

What would it take to build a true “serendipity-maker”?

What if we created a “ChatRoulette for news” that generated content we tended to disagree with — but was also targeted toward our regular levels and sources of news consumption? How hard would it be?

For the last 24 hours or so, the Twitter-sphere has been buzzing over Daniel Vydra’s “serendipity maker,” an off-the-cuff Python hack that draws on the APIs of the Guardian, New York Times, and Australian Broadcasting Corp. in order to create a series of “news roulettes.” In sum, hit a button and you’ll get taken to a totally random New York Times, Guardian, or ABC News story. As the Guardian noted on its technology blog, “the idea came out of a joking remark by Chris Thorpe yesterday in a Guardian presentation by Clay Shirky that what we really need is a ‘Chatroulette for news’”:

After all, we do have loads of interesting content: but the trouble with the way that one tends to trawl the net, and especially newspapers, simply puts paid to the sort of serendipitous discovery of news that the paper form enables by its juxtaposition of possibly unrelated — but potentially important — subjects.

This relates to the much-debated theoretical issue of “news serendipity,” summarized here by Mathew Ingram. In essence, the argument goes that while there is more news on the web, our perspectives on the news are narrower because we only browse the sites we already agree with, or know we already like, or care about. In newspapers, however, we “stumbled upon” (yes, pun intended) things we didn’t care about, or didn’t agree with, in the physical act of turning the page.

As Ryan Sholin has been pointing out all morning on Twitter, the idea of a “serendipity maker” for the web isn’t entirely new. And I don’t know if the current news roulettes really solve the problem journalism theorists are concerned about. So I’d like to know: What would it take to create a news serendipity maker that automatically knew and “factored in” your news consumption patters, but then showed you web content that was the opposite of what you normally consumed?

For example, I’m naturally hostile to the Tea Party as a political organization. What if someone created a roulette that automatically generated news content sympathetic to the Tea Party? And what if they found a way to key it to my news consumption patterns even more strongly, i.e., if somehow the roulette knew I was a regular New York Times reader and would pick Tea Party friendly articles written either by the Times or outlets like the Times (rather than, say, random angry blog posts?)

I think this is interesting, because it would basically hack the entire logic of the web. The beauty of the web is that it can direct you towards ever more finely grained content which is exactly what you want to read. It would somehow know what you wanted even before you did. In other words, it might be the opposite of what Mark S. Luckie called “a Pandora for news.” And it would solve a very real social problem — or at least a highly theorized social problem — what Cass Sunstein calls the drift towards a “Daily Me” or “Daily We,” where we only read news content we already agree with, and our political culture suffers as a result.

So. This is a shout out for news hackers, developers, and others to weigh in: How hard would it be to create a machine like this? How would you do it? Would you do it? I would really like to write a longer post on this, based on your replies. So feel free to chime in in the comments section, or email me directly with your thoughts. I’d like to include them in my next post.

March 04 2010

15:00

The Newsonomics of time-on-site

[Each week, our friend Ken Doctor — author of Newsonomics and longtime watcher of the business side of digital news — writes about the economics of the news business for the Lab.]

Parse out the numbers, and they’re quite puzzling.

The average news reader spends little time on newspaper-owned sites, from a 20 minutes a month or so on the New York Times site to eight to 12 minutes on most local newspaper sites. That’s minutes per month. Those numbers, as tracked by Nielsen and reported monthly by Editor and Publisher, are steady at best, showing, in fact, some recent decline. They are, literally, stuck in time.

Then, take the number of minutes Internet users spend on social sites. Nielsen’s January tally showed seven hours of usage a month on Facebook alone, in the U.S., blowing away all competition. That’s some 40 times more time spent on social sites than on any single news site.

Which is a bit deflating for those in the news business. So let’s try to get at what the numbers may be telling us.

Maybe that big Facebook number isn’t as important as we think. We all have long spent much more time in conversation, much of it idle, some of it about what we’re doing right now or plan to do (the “statusphere” of the pre-digital world) than we have in reading the news. So social-site time may replace water-cooler conversation time. Further, do those Nielsen numbers mean that someone is actively perusing Facebook walls (or Twitter feeds) until their eyes fall out — or that they are keeping windows open on their computers? Are they engaged in a way that advertisers care about?

Then again, if Facebook time is a proxy for our new information centers — where we go to find out what’s happening in the community and the wider world — then it is becoming the new home page. Recall how newspaper sites all put up “make us your home page” buttons more than a decade ago? Constructively, that’s what Facebook done, without the button. That’s not surprising; it’s the ultimate page about what we care about most: me. Sure, some of the posts tell us about the wider world, but a good 80 percent or more tell us something personal.

If social sites, including Twitter, are a new center — Nick Negroponte’s “Daily Me” morphed — that’s a new challenge, and maybe opportunity, for the news industry. The challenge: getting the news to where the readers are hanging out, and figuring out to monetize there. The opportunity: If properly seeded in the social sites, the readers themselves do the (free) marketing and distribution of the content. The early tests of Facebook Connect appear promising here, though too few news companies are experimenting at any kind of scale. (See “The Newsonomics of social media optimization“.)

Now, let’s look at the Newsonomics of time-on-site — how well such time is monetized.

We’ll do some extrapolating with Facebook, to figure out what 2010 might look like. Let’s start with January numbers of 113 million U.S. users and seven hours time spent. Let’s be conservative and say for the year, it ends up with 120 million users and the same seven hours. That’s 84 hours a year for the 120 million, or a little over 10 billion hours of time spent.

For newspapers, let’s use one of the higher-achieving companies for comparison. The New York Times has been averaging about 20 million monthly uniques. It’s time-on-site varies considerably, with the news (!). Let’s give it 25 minutes a month on average. That’s 5 hours a year, or in total, about 100 million hours.

So, in time spent, the Times is less than one percent of Facebook.

Now, let’s look broadly, and quickly, at revenue. The Times’ 2009 digital revenue: about $342 million. Or $3.42 for each hour spent on the site.

Facebook’s revenue numbers are unannounced, but smart industry speculators put its 2010 number at about an even billion dollars. Or about a dime an hour of time spent.

$3.42 vs 10 cents. The Times is monetizing its time on site 34 times better than Facebook.

The Times and other big established news brands will say that’s more than fair, given the attention of the audience, the premium nature of the content and the demographics of the audience. Facebook, and its financial and spiritual advisors, will tell you that’s all upside. They’d point to yesterday’s partnership announcement with (Adobe’s) Omniture on ad placements as just one small step to a large revenue future.

Photo by Robbert van der Steeg used under a Creative Commons license.

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