Archive for the 'streamy' Category

Another boring personalized news service

I love seeing more and more copycat “intelligent” personalized news sites. The good news is that means that there are funders out there who still know in their gut that there’s money to be made on innovation in the news business. They just need the one idea that will stick. And go pop.

Meantime, more than a six months ago, Mike Arrington wrote about a site called Thoof. Back then, I was also writing and thinking about Streamy and FeedEachOther and other unmemorable twists on feed readers and personalized news sites. No matter their differences, they all seem the same. I just came across yet another—Tiinker—and I just can’t bear it any more.

In his write-up of Thoof, Arrington frames the debate as taking place between two competing positions. He believes that “the masses want popular news,” while the Thoof’s CEO believes that “the masses want tailored news.”

I think they’re both wrong and come at the issue the wrong way.

People want their news based on others’ interests—specialized news from friends (those who have similar interests) and widely popular news from the masses (everyone else). And they want their news based on their own interests, even if their friends don’t share those interests.

Now suppose there’s a continuum of users—from RegularJoe on one end to PowerUser on the other.

RegularJoe wants his news from other people. Although he has relatively few “friends” online, and is thinly connected to the ones he has, he wants them to put in most of the effort to help him get specialized news. (He likes read the “Most Emailed” news articles but doesn’t email them, or he likes visiting Digg but doesn’t log in and vote.) RegularJoe is mostly interested in widely popular news.

PowerUser is different and wants his news mostly based on his own interests. But it would be a mistake to think that he pursues his interests alone (no man is an island, says Donne). He has relatively many friends and enjoys pushing and pulling mutually interesting news to and from them. Of course, PowerUser also has news interests that his friends don’t share or don’t share as strongly, and so he pursue his news independently from his friends as well. Because he enjoys consuming a lot of information, moreover, PowerUser is also interested in widely popular news (he wants to keep his finger to the pulse).

These purely black-box algorithmic personalized news sites don’t really fit either guy.

RegularJoe: They’re too hardcore for RegularJoe. He doesn’t want his own news because his interests just aren’t sufficiently deeply cultivated. RegularJoe isn’t motivated enough to build up a profile by clicking “thumbs up” all the time (as tiinker would have him). When he is motivated enough, he isn’t sufficiently consistent over time for these fancy algorithms to get him what he wants before he strays back to cnn.com because it’s easier to let someone else decide (a person-editor, in this case).

PowerUser: They’re too secret for PowerUser. He wants to put in more effort cultivating his interests and doesn’t want to trust an (anti-social) algorithm from some start-up that might disappear tomorrow. PowerUser also wants to get specialized news from niche groups of friends. For him, the fact that friends X, Y, and Z read some blog post makes it inherently more interesting because they can have a conversation about it (broadly speaking). The personalized news sites just aren’t sufficiently social for the PowerUser who wants to interact with friends around the news.

This isn’t meant to be a slam-dunk argument. I’m not sure about what happens with the group of users who are in the hypothetical middle of the continuum. Maybe there’s some number of users (1) who care enough about the news to have non-trivial interests that don’t shift or fade over time but (2) who also don’t care very much for a transparent or social experience of the news. Ultimately, however, I really doubt that this group of users is big enough to support this kind of personalized news site.

Advertisements

If you got excited about Streamy…

…then you should check out FeedEachOther. That’s what Marshall Kilpatrick of R/WW says. If you were let down with Streamy, on the other hand, it looks like you will also be let down by FeedEachOther.

What’s the bummer? These “feature-rich super-social RSS readers” just aren’t that feature-rich or social. They’re just not so different from Google Reader. They’re still RSS readers.

But first the good news. The thing pulls comments from the original blog into the reader. That’s awesome. Multiple kinds of relationship are good too.

I don’t want to subscribe to “similar” feeds according to some recommendation that’s a huge black box. In fact, it doesn’t really even work, and its black-boxiness prevents me from knowing why. Why, for instance, does FeedEachOther only give me recommendation based on the whole feed? Why not on each post? Whole feeds contains posts way too diverse to derive sufficiently sufficient semantic patterns from them.

It’s not okay to look at all of Jeff Jarvis’s feed and offer me this string of banal tags: “advertizing – buzz – internet – news – technology – blogs – daily – marketing – politics – web – blog – commentary – jarvis – online – trends – business – imported – media – tech – web2.0 – blogging – culture – journalism – opinion – tv.” Setting aside the problem of blogs-blog-blogging, it’s not okay because they’re so generic and because I can’t stack them up and take their intersections. I can’s use these tags the way the people who created them use them. When someone in delicious tags something “journalism,” they might also tag it “trends.” Neither topic is interesting alone; only together are they interesting. (Indeed, ‘trends in journalism’ is very interesting.)

Plus! On top of reading each post’s comments with a feed, I can share notes and items within the system. But wait! “The only thing better” would be to post comments from the web app to the original post? Actually, that’s a lot better. That’s worlds and worlds better. A web app is still just a basic RSS reader until it can weave itself into the same cloth of which the many, many thousands of blogs with their comments are made.

So, no, “the absence of offline and mobile modes, weaker analytics than Google Reader offers and a limit of 500 feeds by OPML import” are not the “only shortcomings.” Someone’s seriously drinking the RSS Reader Kool-Aid. And that’s too bad—because RSS itself is so many times greater and more magnificent.

In the end, Google Reader, Streamy, and FeedEachOther are bastions of only ONE component of networked news. They allow readers to network the news by publisher. Sure, they do more than dabble in allowing readers to network by fellow readers. There’s got to be more though—comments from reader to blog would be a big step. Lastly, both Streamy and FeedEachOther just don’t have the necessary kind of semantic (or “Semantic”) insight into their content yet. The three components of networked news must be as one for any to be truly worthwhile.

When will my news platform serve me up content that’s from my favorite author and recommended by my good buddy and about my favorite subject or story or beat? When that happens, we’ll not only all be reading our own really interesting stuff—we’ll care enough about it to get into even more interesting conversations.

O Streamy, Where Art Thou?

StreamyMy traffic stats tell me that streamy.com refers a few readers to my blog every so often. I think it’s great that a few people are reading my blog from Streamy. When do I get an invitation and the accompanying ability to read my blog and others there? I really want to know to what extent it’s a network of readers and a network of the people and the issues in the news.

I’m hopeful for the former but will be surprised if Streamy’s “filters” can master the latter.

Applying the Three Components of Networked News

For a goodly time now, expect to see this blog try to flesh out this concept of networked news by reviewing isites that concern themselves with the news, either completely or substantially—from the New York Times to digg to Google Reader to Mario Romero’s awesome Google Reader Shared Items app for Facebook to Topix to Memeorandum to Pageflakes to Thoof to Streamy to whatever else with which I may cross paths.

I’ve got my three metrics, and it’s time to make sense of them. Maybe along the way we’ll figure out what some bright person could do to satisfy Arrington’s appropriately underwhelmed feeling about online news. Maybe we’ll figure out that “networked journalism” has something to do with networked news. Maybe not.

But what’s first?

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 newassignment.net 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.

Ornery Arrington on Personalized News

streamyI can’t get enough of how Michael Arrington, at TechCrunch, rags on personalized new sites. I love it. Talking about the newest venture to join the hunt for a killer solution to online news, Arrington writes of Streamy, “It’s pretty and extremely well thought-out, but it’s not clear that it does anything new enough to grab people’s attention.” Plus, “It is well designed, has lots of intelligent features, and is almost sure to drop into obscurity immediately after launch.” What a guy!

For now, I’ll withhold real judgment—especially of the claims made here—till I’ve had a chance to check out the private beta, to which I’ve requested an invitation.

Meantime, I’m impressed with the social networking and what they call “filters,” which are essentially substance- and source-based ways browse, and subscribe to, kinds of content, by keyword and original author, respectively. Ideally, that would mean that someone could set up his personalized page to pull in everything Arrington says about, say, “personalized news.” The trick, then, is how social networking brings the virus to the filter. Your friend’s becomes your filter and then it becomes my filter; my filter becomes yours, your friend’s, his friend’s, and so on.

Note that amateurs don’t have to control these filters either. Arrington could promote his own, using them to help him slice up his content along different lines, potentially overlapping lines, and push it out Streamy readers of news, if there ever are any. Or these filters could allow someone to become an editor, much the way Scoble acts as an editor (choosing the news) with what he calls his link blog. If I were running Streamy, I’d be thinking about how I could allow users to monetize their filters. They are, after all, just platforms for subscriptions. Find a way to allow an expert on some tricky topic like global warming sell you his daily digest of the best reading on climate change. He could write his own original material as well, of course, and include it in his filter.

I agree with Arrington that integrating IM is smart, and integrating the ability to drag and drop stories is super smart. I wonder how popular it will become for sites to integrate IM. Will the New York Times have it some day? Will espn.com? It seems to make sense to distribute IM over virtual locations rather than keep it all cooped up in one place. If I were running meebo, I’d be thinking about how I could build a proprietary web-based IM client just for the New York Times. (From what I can tell, Jake Jarvis has tried to turn meebo into a Facebook app. I signed up, but got an error: “There are still a few kinks Facebook and the makers of Meebo are trying to iron out….”) I love meebo almost as much as Arrington’s orneriness.

Here’s the screencast of Streamy:


Josh Young's Facebook profile

What I’m thinking

Error: Twitter did not respond. Please wait a few minutes and refresh this page.

What I'm saving.

RSS What I’m reading.

  • An error has occurred; the feed is probably down. Try again later.
Advertisements