Archive for the 'JeffJarvis' Category

What Is Networked News?

Networked news describes a structure for consuming information. It means pulling in your news from a network of publishers—bloggers and traditional news outlets. It means pulling in your news from a network of readers—friends and experts and so on. And, crucially, networked news means breaking down the bits of content into their relevant constitutive pieces and reforming those pieces back into their own network. It means pulling in your news from a data-driven network of the people and the issues in the newspeople like George W. Bush and Steve Jobs and Oprah and issues and memes from “republican” and “iraq war” and “campaign 2008” to “iPhone” to “power of forgiveness.”

The concept of networked news grows out of the realization that the stories we care about exist between one author and another, between articles and blog posts, between newspapers and blogs. The story is a kind of thread that runs through time and in and out of the person-subjects and issue-topics of the news.

Networked news is not networked journalism, which is a structure for publishing information. See pressthink, buzzmachine, and for that parallel “genius” project to grow and diversify the number of sources from which we pull our news.

NewsmapThe first and second components of networked news are new but not unprecedented. Pulling in your news from a network of publishers is what we do when we subscribe to RSS feeds and read them in one place. It’s the river of news I read when I fire up Google Reader, which gives me news about the tech industry, about finance, and about politics. Techmeme, Memeorandum, Google News, and other memetrackers are other great examples of networking news from publishers. Newsmap, based on Google News, is the picture of this first component. Thoof and other news-focused web apps with similar recommendation engines also represent this publisher-based side of networked news.

Pulling in your news from a network of other readers is what Mario Romero is working on with his Google Reader Shared Items application for facebook. It’s also what Digg and others represent.

There are sites that represent both the first and second components of networked news. It’s what Newsvine, Topix, Daylife, and others represent. It’s what Pageflakes, Netvibes, iGoogle and others represent. Though I haven’t actually toyed with the site yet (I’m still waiting on that invite, guys) it looks like Streamy sits at the current bleeding edge of the reader-based front of networked news.

The third component of networked news is, in some ways, the oldest, represented by simple searches to Google News or Technorati tags. It’s also the most difficult component—technically, socially, you name it. When I encourage Mario to let users browse his Google Reader Shared Items by tag, I’m encouraging him to let us readers of news pull in bits of content by issue and meme. When Streamy claims to have “filters”—which I called “substance- and source-based ways browse, and subscribe to, kinds of content, by keyword and original author, respectively”—it’s claiming to have taken a few steps into the this elusive third component of networked news.

networkOne kind representation of this third component, in the form of how Exxon putatively buys scientific research, is graphic. The “story” is the whole visual network, while the actors are broken down and interconnected within it. The bits of content, in this case, come in the form of profiles on each actor pictured. People and foundations are linked up by bridges connecting them. Those bridges, exxonsecrets says, represent the money that Exxon funnels through the foundations to pay the people to conduct and promote bogus climate research. Users can create, manipulate, and save their own graphical network maps for all to see.

A swirl of excited ideas in my head, it’s all rather tough to articulate. But I’ll get to it soon enough, bit by bit.

Google Reader Shared Items Needs Fewer Friends

I have only one “friend” who has the application. That’s Robert Scoble, and I’d rather browse his link blog in Google Reader itself. There’s no reason for me to check it out in facebook.

There’s a mismatch between a facebook friend, who’s someone I usually know personally and often care about a great deal, and someone whom I’d like to include in the limited group of people whose Google Reader preferences I care about.

I’d love it if lots of my favorite bloggers kept “shared” their favorite posts and brought all that into facebook. I’d love to have Jeff Jarvis’s favorite reads. I’d love to have Doc Searls’s and Dave Winer’s. Yada yada.

But I’m not sure I want them to be my facebook friends. I don’t know them, haven’t met them. Equally as true, if not more, is that they are unlikely to want me to be their facebook friend.

The Google Reader Shared Items application should move away from the conception of “friend” native to facebook. Call the new conception a “follower,” and don’t allow the followed any choice, once they’ve hit shift+s in Google Reader, about whether I snoop in on what they’re reading. After all, I don’t have to know, or even like, Scoble to pull the feed for his link blog into my Google Reader.

I want to use this facebook app to actively subscribe to many individual’s shared items feeds. That’s because, in the end, there’s really only one important feature the app needs: aggregation how I want to aggregate.

Maybe that’s by tag. Maybe that’s by my favorite tech bloggers. Maybe the time comes when I can pull together the recommended reads from my favorite dozen political blogs—Think Progress, Matt Yglesias, Josh Marshal, Kevin Drum, Scott Horton, and others. Maybe I want to aggregate by my best friends forever. It should be up to me.

Grokky Jarvis Has Something to Say about the News

Jeff JarvisJarvis is correct. Equally important in the land of new ideas, however, is vivid articulation. Write the truth, and write it well.

And so he does. To wit, “Like most everyone else chasing this golden fleece, I’ve defined [hyperlocal news] as content, news, a product, listings, data, software, sites, ads. It’s not. Local is people: who knows what, who knows whom, who’s doing what (and, yes, who’s doing whom). The question should be…how we bring them elegant organization.” That’s Zuckerberg’s term—elegant organization. Jarvis likes it a lot. He’ll tell you about it too.

“I now believe that he who figures out how to help people organize themselves,” Jarvis continues, “letting them connect with one other and what they all know, will end up with news, listings, reviews, data, gossip, and more as byproducts.”

I’ll take it from here. The generally news-based web application must organize its information around functional units that are most relevant to the subject. When the subject is news, the most relevant functional units are people and and issues and organizations. Note that a full thirty percent of google searches are for people, for instance, says Jaideep Singh, CEO of Spock in this July 2 PodTech video. Also note the proliferation of person-centric search engines, like Spock, ZabaSearch, Pipl, PeekYou, and Ligit, to name a quick few.

Today, however, the news is still fundamentally organized around its content, its tiny bits of content, its data, whether those be newspaper articles, blog posts, podcasts, or webpages. That organization—in which people and issues are contingent upon the bits of content that discuss them—is a relic of paper and, just as important, html. The article has taken the story hostage. That must be turned on its head: the bits of content must be contingent on the people they discuss. The people, and also the issues, who constitute the story, as it were, must be liberated from the confines of the article. That’s the promise the internet makes to journalism in the twenty-first century. That’s the promise the database makes to news.

A newspaper article will get broken into pieces, like legos that interlock: “little objects,” as Scoble once called them. Those objects will be stored individually, deployable individually, graphable individually. Individually, but not alone. They will live in cells among millions of others cells, part of semantic hive buzzing with the fervor of the world’s news. Or at least the world’s news according the internet.

By slicing up the data, by breaking up the data, we can put it back together. Only we can put it back together however we like, as individuals and as a collective—confident in our ability to tell whatever story may yet be lurking in the interstices of modern journalism. Blogs created an army of journalists. The web needs an application that will arm a legion of editors, each driven largely by their own individual tastes for consuming news but cooking up social feast of intelligent information.

Jarvis again: “People, not content. People, not data. People, not software.” Wait, not software? Getting a bit carried away is a small price to pay for generating so much momentum in the first place.

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