This is why I want to make maps of global news output: real-time visualizations of every article recently produced, clustered by links or co-consumption. Then mark the articles that I’ve read in a different color — a “you are here” marker.

I bet most people would see that they never leave their home town in information space. Call it a curiosity generator, just like a map of the world.

I developed this idea in some detail in a 2009 post, “Mapping the Daily Me.”

Perhaps one way to look at this is to pose the question: Can the Web be semantic and serendipitous at the same time?

That is, on the one hand we want a system that knows us: our interests, our browsing history, our likes and dislikes. But on the other, the engine has to be unpredictable enough that it gives us a sprinkling of *good material* that we might not otherwise have found. (I put emphasis on “good” because, as Howard Owens pointed out above, randomness does not equal “news serendipity,” which in the traditional sense implies some kind of vetting for quality, making the newspaper, for example, a serendipitous assortment of reasonably good stuff.)

As others have mentioned, I have problems with the false binaries associated with “give me the opposite” kind of serendipitous news. But, at the same time, what I *would* like to see is a function for getting stories that really explain where other sides are coming from on an issue. Take the Tea Party, for example. If I’m anti-Tea Party, don’t just give me a story that’s sympathetic to its anti-government rhetoric. Instead, give me an “explainer” that helps me come to understand *why* Tea Partiers feel the way they do — not simply the *what* that is usually what you find in news stories (e.g., images of protest, soundbite claims, etc.).

As Matt Thompson’s SXSW panel talked about, the Web can do so much more in giving us the crucial context to make sense of our world. Why not build a system that does both — that is explanatory and “multiperspectival” (as Gans put it)? Rather than just get the headline version of “the other side(s)” to the story, let’s see if we can’t gain a better appreciation in the process about where they’re coming from.

We can imagine, anyway.

But you can also create bundles of feeds on Google Reader to subscribe to with a single click. So what if you get your conservative/old/different in whatever way friend to make a bundle and run it through the Play filter?

Perhaps a bit long winded but it might work quite well.

So we want a system that builds a profile of you and what you like a-la SumbleUpon but also builds a profile of who your opposite is. And then every X links it drops something that your nemesis might really enjoy. Your nemesis is not your opposite, just someone like you in most ways but very different in a few critical (in this case political) ways.

Another option would be a system like that described in the UltraGleeper paper: http://www.crummy.com/software/UltraGleeper/IntroPaper.html

Specifically the Indie Rock Peter Principle that’s described where certain attributes when they pass a threshold of agreement begin to decrease the score of something. In the paper it’s used to avoid showing you obvious links but it could similarly be used to avoid preaching to the choir.

My hunch is that what we would find is also my own critical comment on the project: my guess is no one political leaning would be better suited than another. Moreover that binary oppositions would start to break down through a meta-level analysis of what attitudes we harbor toward opposition news.

To the point, namely that there are, obviously, multiple parties and perspectives at play around every news event. I am not sure an opposition news tool is really what we want. We may want a serendipity news tool that exposes the reader not only to the opposite viewpoint, which may be inferred anyways, but to wholly fresh, third, fourth, or fifth points of view. Two-party oppositions do not recognize the Archimedean point from which the opposition itself begins to make sense.

Two cheers for deliberate serendipity, and only one for seeing only the other side. From a technical point of view, neither seem in the slightest impossible. If anything, in fact, “not what I expect” is probably much easier to produce than “the opposite of what I want.”

Hope to hear more about this. Very promising kernel.

Serendipity ≠ random.

For serendipitous news to have value it needs to delight and engage readers with information that otherwise wouldn’t have encountered. That takes more than algorithmic randomness.

ChatRoulette is offering an experience that millions of people want, the chance to run into someone whose views or actions you cannot publicly endorse despite being very interested in them. ChatRoulette’s randomness takes all the blame off your shoulders. If you land on a naked dude, you can blame ChatRoulette, not yourself, but rest assured, you knew there were naked dudes on ChatRoulette.

It’s also a lot of fun and something to do with friends.

I don’t see how this translates to news. To echo Susannah, above, this sounds kind of boring and “eat your vegetables-y.”

I like the Guardian model in that it’s random but also limited (by what’s in that paper). I think a ChatRoulette for news would be great if it would allow users to set some parameters (maybe dates, subjects, places?) that are specific enough to generate interest, but still broad enough to allow for surprise.

If you include a variety of sources and filter topics based on current best search technology (no where near close to “somehow knows what you wanted”), you will naturally get serendipity and plenty of context in the content that matches. So it’s not as easy as you might think to isolate yourself i.e. I agree with your adjusted statement of “highly theorized social problem.”

We think we’ve created a reasonable Pandora for News experience in our current service at http://www.icurrent.com. And it doesn’t seem creating insularity or losing serendipity will be problems.

My other concern is that serendipity debates tend to be reduced down to left-right debates. It’s “liberals should watch Fox” and “conservatives should read The Nation.” I think that artificial dualism is one of the least appealing tropes of traditional journalism — the idea that there are two sides to be represented in stories, or that the world can be nearly broken into “Tea Party friendly” and “Tea Party unfriendly” stories. I’d argue that true serendipity comes from things that don’t fall neatly into that rubric at all. The world isn’t just about politics. If you read a lot of Dem-loving blogs and a lot of GOP-loving blogs, your news diet is still radically oversaturated with white college-educated DC men with bad hair and Model UN trophies back home.

Buttons on the toolbar = Thumbs Up, Thumbs Down, Random, and “Make Me Uncomfortable.” How does the system measure what makes you uncomfortable? Well, it can’t just be based on everything you dislike. It’s going to need more data than that.

Maybe instead of “uncomfortable” the action is “show me the opposite of this,” but that still assumes more variables than just thumbs will provide.

Maybe Facebook has enough data on us to build this? Who else?