Archive for the 'TechCrunch' 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.

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Sell me tags, Twine!

How much would, say, the New York Times have to pay to have the entirety of its newspaper analyzed and annotated every day?

The question is not hypothetical.

The librarians could go home, and fancy machine learning and natural language processing could step in and start extracting entities and tagging content. Hi, did you know Bill Clinton is William Jefferson Clinton but not Senator Clinton?! Hey there, eh, did you know that Harlem is in New York City?! Oh, ya, did you know that Republicans and Democrats are politicians, who are the silly people running around playing something called politics?!

Twine could tell you all that. Well, they say they can, but they won’t invite me to their private party! And maybe the librarians wouldn’t have to go home. Maybe they could monitor (weave?) the Twine and help it out when it falls down (frays?).

I want to buy Twine’s smarts, its fun tags. I’d pay a heckuva lot for really precociously smart annotation! They say, after all, that it will be an open platfrom from which we can all export our data. Just, please, bloat out all my content with as much metadata as you can smartly muster! Por favor, sir! You are my tagging engine—now get running!

What if Twine could tag all the news that’s fit to read? It would be a fun newspaper. Maybe I’d subscribe to all the little bits of content tagged both “Barack Obama” and “president.” Or maybe I’d subscribe to all the local blog posts and newspaper articles and videos tagged “Harlem” and “restaurant”—but only if those bits of content were already enjoyed by one of my two hundred closest friends in the world.

I’d need a really smart and intuitive interface to make sense of this new way of approaching the news. Some online form of newsprint just wouldn’t cut it. I’d need a news graph, for sure.

See TechCrunch’s write-up, Read/Write Web’s, and Nick Carr’s too.

PS. Or I’ll just build my own tagging engine. It’ll probably be better because I can specifically build it to reflect the nature of news.

Loving aideRSS

Tough love, that is—there’s a lot more I want out of this.

But first, aideRSS is awesome. When I serve it a blog’s feed, it looks at how many comments, delicious saves, and other mentions each post has and then divides them up according to their popularity relative to one another. AideRSS offers me a feed for each division—the smallest circle of the “best posts,” a larger circle of “great posts,” and an even larger circle of “good posts.”

I’ve got two main uses for it. It ups the signal-to-noise ratio on blogs that aren’t worth reading in their filtered state, given my peculiar tastes. And it allows me to keep current with the most popular posts of blogs I don’t have time to read every single day. That’s huge.

There are real problems, however, and other curious behaviors.

Consider Marc Andreessen’s blog pmarca. For one, AideRSS strips out his byline (here’s the “good” feed). For two, it has recently really oddly clipped his most recent posts and made them partial feeds (I also follow Andreessen’s full feed, and it is still full). Also, aideRSS also seems to strip out all the original dates and replace them with some date of its own.

That’s a problem. Google Reader published Andreessen’s post called “Fun with Hedge Funds: Catfight!” on August 16, 2007. But it’s the most recent post in AideRSS’s filtered feed of Andreessen’s “good” posts. The problem is that it follows “The Pmarca Guide to Startups, part 8” in the “good” feed but precedes it in the regular feed.

Did the post about the hedge funds and the cat fight receive some very recent comments, more than a few days after it was first published? All else equal, it wouldn’t be a problem to have the posts out of order—that would seem to be the sometimes inevitable result of late-coming comments or delayed delicious saves, etc. But all else is not equal—because the original dates are stripped. Posts in a blog exist relative to one another in time. Stripping out the dates and then reordering the posts smothers those important relationships.

But let’s look to the horizon. AideRSS can’t handle amalgamated feeds. I want to serve it what Scoble calls his link blog—the feed of all the very many items he shares in Google Reader—and receive only the most popular. That way, I would get the benefit of two different kinds of networked news at once. I’d get the intersection of the crowd’s opinion and the trusted expert’s opinion.

I’d also like to serve it a big mashup of lots of feeds—say, my favorite five hundred, routed through Pipes—and have it return the top two percent of all posts. That kind of service could compete with Techmeme, but it could be dynamic. We could all build our own personalized versions of Techmeme. That would be huge.

Trying it out a few different ways gave wild results. The posts in an amalgamated feed weren’t exactly being compared to one another on a level playing field—so that even a relatively bad TechCrunch post with ten comments crushes an small-time blogger’s amazing post with eight comments. But they also weren’t being compared to one another only by way of their numerical rankings derived from their first being compared to the other posts in their original feed.

Why can’t aideRSS measure each post’s popularity with respect to its kin even when it’s among strangers? The share function within Google Reader gives aideRSS the original url for each post. Can’t aideRSS take the original url for each post, find the original feed for each post, and then analyze each post against the other posts in its original feed? That would be much more analysis, for sure, but it would also be much more valuable. I’d love to see it.

Of course, while it may be a surprise or unintuitive at first, all this is really just one particular take on the first and second components of networked news—pulling in your news from a network of publishers and from a network of readers, including friends and experts and others. Without my additions, aideRSS represents just the second component, in which we get news based on whether others are reading it and participating in the conversation around it. My additions bring a little of the first component.

UPDATE: It would also be awesome to serve aideRSS the feed generated by a WordPress tag or by a persistent Google News search. That would be bringing in a shade of the third component of networked news.

Facebook Hacked? My Identity Too?

So very many people use facebook. So very many people, though they may not realize it, rely on facebook to establish a real presence of themselves for others to see. That presence happens to be online, but no matter. It’s identity.

That’s why it may shock very many people that they have put their identities in the hands of a private company—one that seeks profit, naturally enough—the guts of whose website has been revealed. Techcrunch says that just “a quick glance” reveals “hidden aspects of the platform” that “give a potential attacker a good head start.” That said, many of the comments on that post take the whole thing to be a hoax.

Anyhow, note that facebook seems to have a comment at Techcrunch verifying a problem. If the comment had been left at Google News, would there be any doubt?

It doesn’t make much sense to wonder whether Web 2.0 projects like facebook are “due” for some wildly major breach, for lots of reasons, like the fact that no particular person with a facebook profile is due for such a serious intrusion. So far, so good….

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?

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:

Thoof Is Close But Not Nearly Close Enough

ThoofI think recently launched online news site thoof has taken another step in the right direction—toward giving its readers the news they want and withholding the news they don’t. Thoof seems to learn what its readers like buy remembering their clicks on article summaries that given user-assigned and -edited tags. If you click on an article summary with the tag “politics,” the next time you visit you’re more likely to see article summaries tagged “politics.”

But Mike Arrington’s concern, inspired the fact that “web is littered with failed or stagnant personalized news startups,” is still relevant. People do “usually want to read news and then discuss it with friends. That is why people still tend to prefer big news sites: “everyone else flocks there, too.”

If it wanted to, however, Thoof could keep something like main page that displayed the aggregate of all its readers’ preferences. Each reader could then, at any time, choose whether to read his personal page or the page that reflects the many, many decisions of the Thoof community. Then Thoof might be able to satisfy Arrington’s worry that “the niche audiences that really want personalized news aren’t enough to sustain these startups.” Thoof can have it both ways.

Better, in fact. Readers who want the news the “flock” sees get a much purer version of it, an elevated version of that. The flock isn’t just reading the same thing—they’re causing themselves to read the same thing along the way. They’re not just readers, led by a shepherd. They’re editors, and they lead themselves.


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