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I’m Doubling Down My Subscriptions Because of FriendFeed Lists

As discussed here before, FriendFeed’s beta version includes the ability to tag users, putting them in different Lists you create. You can create your own programming channels.

I’m loving this feature.

One effect for me has to been to add subscriptions left and right. Why? Two reasons:

  1. Now that I’ve got themed Lists, I want there to be some good content in them! Right now, I’m subscribing to a lot of FriendFeeders who are into Enterprise 2.0 or who have an amazing eye for pictures.
  2. Managing a high flow of content is a lot easier. You can take users out of your Home feed, and tag them into different Lists. Check the Lists at your leisure, and you can see content for many, many more people. It doesn’t all just go flying by you.

Here’s my rendition of how Lists have changed the FriendFeed experience:

How about you? You started your Lists yet?

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See this post on FriendFeed: http://friendfeed.com/search?q=%22I%E2%80%99m+Doubling+Down+My+Subscriptions+Because+of+FriendFeed+Lists%22&public=1

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Nick Carr: Google Making Us Stupid? How About Smarter?

The media or other technologies we use in learning the craft of reading play an important part in shaping the neural circuits inside our brains.

Nick Carr, “Is Google Making Us Stupid?”, The Atlantic, July/August 2008

Nick Carr has a really interesting piece in the current issue of The Atlantic (CNET coverage here). The premise of the article is that use of the web is possibly rewiring our modes of thinking. We’ve become much more adept at the light skimming of content than the deeper understanding of long thought pieces. If that’s the case, what does that mean mean for intellectual progress in the future?

The article is full of historical references (e.g. how Friedrich Nietzsche’s writing changed when he went to the typewriter) and scientific studies (e.g. the plasticity of the human brain enables us to adapt to new learning modes).

One area that Nick doesn’t talk about much is apophenia, which Maki on FriendFeed first alerted me to. According to Wikipedia:

Apophenia is the experience of seeing patterns or connections in random or meaningless data. The term was coined in 1958 by Klaus Conrad, who defined it as the “unmotivated seeing of connections” accompanied by a “specific experience of an abnormal meaningfulness”.

Robert Scoble employs apophenia as part of his profession. In one of his posts, he says: “I like the noise. Why? Because I can see patterns before anyone else.”

In this way, the larger consumption of data in lightweight chunks can be thought to bring a new kind of intelligence to people. Your subconscious is collecting a series of signals along the way. At some point, all of this information lurking just below your accessible thought pops up, and you’re suddenly aware of an emerging dynamic.

I really like this idea. And it fits with how we pick up information ourselves in the physical world. You don’t stop and ask people what they’re talking about on the street. But you may pick something up as you listen in to their conversations. You may not read the planning commission report, but you see how development is progressing in your town based on the construction you see.

I’ll contrast apophenia with traditional learning, in which a person can go deep with the thinking of a few selected masters in a field. But I draw this contrast not to dismiss traditional learning. Not at all. Understanding things based on a deeper reading of learned intellectuals and practitioners is a vital part of learning.

I hope Nick is wrong about losing our ability to sit through a longer piece. I haven’t lost that – I read his article twice this weekend.

If we can add a new mode of learning via apophenia to our traditional forms of undersatnding concepts, we’re all going to be smarter in the long run.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Nick+Carr%3A+Google+Making+Us+Stupid%3F+How+About+Smarter%3F%22&public=1

Three Big Questions Facing FriendFeed

I write about FriendFeed. A lot. Someone told me they wondered if I was employed there. Nope, just really enjoying the service.

Then I see a couple of bigger names in the online world, Robert Seidman and Steve Rubel, expressing their view that FriendFeed feels like it’s going to be the next big thing.

And I realize I’m not the only one with great enthusiasm. It’s growing.

As FriendFeed continues to acquire new users, innovate and roll out new features, it’s inevitable that some big decisions will need to be made. I want to discuss three of them here. Shall we?

1. How Will FriendFeed Balance Signal, Discovery and Noise?

This question really hits on two fundamental elements of the social media experience:

  • Distribution of information
  • Consumption of information

Managing information is a BIG deal. It’s hard to get the balance right – when do users really need a piece of info, when are they in the mood for a bit of discovery and at what point do they tune out because of information overload?

Google’s success was in recognizing the need for better information access, a process they continue to refine and improve. The thing with Google is that you search when you have a defined need. User intent is known. It’s what makes Google’s advertising so successful.

FriendFeed has a bigger challenge. Intentions vary by person. By hour. There’s time the river of content needs to deliver a hard dose of signal. Other times, you need a break from some work you’re doing, and you want a bit of discovery. But above all, please recognize what I consider to be noise!

So FriendFeed has to figure out the user intention, a burden that Google doesn’t have.

They’re off to a great start with these:

  • You choose the people to whom you subscribe, providing the first cut on topics you’ll see
  • Excellent Hide function
  • Rooms to isolate discussions around topics
  • Ability to view top content by likes, comments and other signals

This will be an ongoing war for FriendFeed, particularly as the service grows beyond its information junkie user base.

2. How Much of a Social Network Does FriendFeed Want to Be?

FriendFeed states their mission as follows:

FriendFeed enables you to keep up-to-date on the web pages, photos, videos and music that your friends and family are sharing. It offers a unique way to discover and discuss information among friends.

A simple goal. And yet, early users of FriendFeed are finding the social network aspects of FriendFeed to be compelling. I personally have established a completely different network of people on FriendFeed from what I have on Facebook or LinkedIn. I didn’t just port over my friends from those services, I established new connections.

When I was training for my first marathon back in 2003, I regularly participated over on Runner’s World message board. A group of us were running the California International Marathon in Sacramento, and an online bond formed. We conversed on the message board, and decided to meet up in Sacramento. How’d we do it? One guy posted his disguised email address, and we all emailed him. We then did the email thing to coordinate.

FriendFeed is above that level of social networking right now, but not by a whole lot.

FriendFeed has the potential to be a very powerful social network, one rivaling Facebook and LinkedIn. Why? Facebook is your network from school. LinkedIn is your network from work. FriendFeed is your network based on stuff that interests you. That’s what makes it so powerful.

Remember the interest in felix’s FriendFeed Likes Compatibility Calculator? People were really curious about who they match up with based on shared interests.

A few things come to mind as “best of” elements of social networks:

  • Direct messaging (Facebook, LinkedIn, Twitter all provide this)
  • Profile page – express yourself, complements your content, Likes and Comments
  • Status – for those times when you’re just not around or you need to get personal

Want to take it further? I can see FriendFeed becoming a more robust professional network than LinkedIn. You like all those comments and content? Maybe you’d look at that person as a potential hire. How about calendaring? Coordinate events, and it’d be a real nice complement to the Rooms.

How far does FriendFeed want to go in social networking?

3. How Will FriendFeed Make Money?

Ah, the money question. It’s inevitable and ultimately must be addressed to justify the venture capital.

I can see two possibilities for making money at this very early stage in the company’s history:

  • Advertising (duh…)
  • Business uses

Social media advertising has potential, but is not without its issues.

FriendFeed has a a few things to address and going for it when it comes to advertising. Users’ affection for the Refresh function means a lot of page views, but how much time will they spend on the ads. There’s a field of white space off the right, so real estate for ads won’t be a problem.

But FriendFeed does have two good weapons in its arsenal when it comes to advertising:

  1. A search function with a ton of potential (and search is the killer advertising feature)
  2. A mountain of data about what users’ interests are

As for business uses, my first thought when I saw the Rooms feature was that it could be a great thing for companies to use. Employees can trade thoughts on ideas and projects via Rooms. In fact, that’s how the FriendFeed guys use Rooms:

It started when we wanted a better way to share feature ideas and product plans with each other here at FriendFeed

I can also see media companies adding Rooms functionality to their sites. A much richer way to let readers discuss content than the current commenting systems.

Final Thoughts

I’ve written plenty about FriendFeed, and I’ll probably write more in the future. Partly because it’s such a compelling site for me. As a full participant, I can see a lot of stuff going on. And it doesn’t hurt that the site is getting hot in the blogosphere.

But there’s something deeper here as well. In FriendFeed, you can see some of the bigger issues that all social media have to deal with. For instance, I’d written a series of posts about the noise issue on FriendFeed. My most recent post stepped away from being FriendFeed-specific, and took a look at the broader issue of signal vs discovery in social media. Marshall Kirkpatrick of ReadWriteWeb took it a step further with a great post Why Online “Noise” Is Good for You, pulling in scientific studies on the value of noise and discovery.

FriendFeed is tackling some meaty issues, as described above. Since they’ve got traction, a talented team, an innovative spirit and an attentive audience, their efforts to address the big questions will be a terrific study of the larger social media realm.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22three+big+questions+facing+friendfeed%22&public=1

Weekly Recap 060608: Ferris Bueller Was Right

The week that was…

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“Life moves pretty fast. If you don’t stop and look around once in a while, you could miss it.”

Ferris Beuller, Ferris Bueller’s Day Off

Consider that line in the context of the recurring demand for more signal

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FriendFeed rolled out a new feature to let you see the content that has risen above the noise…Personalized recommendations let you see the stuff that has the most likes and comments, but only for content provided by your network…actually, upon closer inspection, there’s one other component to the ranking…from the blog post: “based on your friends’ comments and ‘likes’ and other signals”…other signals?…hmmm…wonder what those are…

It’s a very cool feature, with some real potential…early benefit seems to be finding the good stuff missed during extended time away from FriendFeed (like more than 2 hours)…it also gives you a personal meme as well…

Robert Seidman has a good post describing potential pitfalls…

What winds up happening is that people are finding “best of” items so easily that they naturally are and adding more “likes” and comments to them which causes them to jump to the top of my regular FriendFeed stream (even outside of “show best of”). I don’t love this.

I noticed this too…older posts with lots of likes/comments suddenly were showing up in my stream again…because people using the “best of” feature were liking and commenting…let’s see how the dust settles once people get used to it…

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Robert Scoble, on the value of noise

If you don’t have noise, how can you tell what is signal?

Stop and think about that for a little while…

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I’ve been harping on the noise and filter issue for a while…I was really stoked to see ReadWriteWeb’s Marshall Kirkpatrick pick up the issue with a beautiful blog post Why Online “Noise” is Good For You…a few good points Marshall brings up…

  • Scanning quickly over large quantities of roughly relevant information can turn up invaluable resources, opportunities, context and contacts.
  • The ability to recall passively collected information that was gathered purposelessly in the past and put it to use in the future is a particularly powerful form of intelligence.
  • Some people worry that being exposed to too much information will lead to not remembering very much of it. Scientists say that’s not necessarily the case, though.

There’s a lot more there, you’ll kick yourself later if you don’t read it…

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Plurkkarma“…gonna wait on this one…

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Had a chance to visit the FriendFeed office this week during their open house…if you’ve seen Robert Scoble’s Qik video, you’ve got a good sense of their office space…big, spacious, plenty of room to grow…they actually share the space with another company…

Paul, Bret, Kevin, Casey, Ross, Dan, Ana (bios here) were all just as nice as can be…I’ve actually never gone to one of these start-up open houses before, is this some sort of Valley tradition?…one thing I got from talking with Paul was his interest in the distribution and consumption of information, which is what FriendFeed is all about…

Got to meet a few folks I’ve seen online…Ginger Makela, Adam Lasnik, Adam KazwellLouis Gray was there, and he had this awesome shirt that has his blog graphic on it…it actually made it easier to identify him if you’ve never met him before…as Chris Brogan’s been writing, you need to establish your online brand (even in offline meetings)…

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Weekly+Recap+060608+Ferris+Bueller+Was+Right%22&public=1

A Definition of Noise

FriendFeed co-founder Bret Taylor has a nice interview with CNET’s Dan Farber today. In the interview, Bret mentions that FriendFeed will be introducing ranking algorithms soon. These will create your own personalized FeedMeme.  Which is going to be interesting. Dan Farber then asks whether user controls over content will be rolled soon. Bret answers ‘no’.

In the discussion around this link to the interview, Kingsley Joseph comments:

great interview. Bret’s got it right – ranking algorithms, not filtering is the key to noise processing

This was an interesting comment. I think of noise as a very personal thing. And the ability to define your own take for what constitutes noise makes sense to me. But Kingsley has a different point of view.

So I wondered…are we talking about the same thing. What exactly is noise?

A Definition of Noise

The diagram below is my definition of noise.

Signal is all about the stuff you actually want. For some, it’s a steady stream of social media entries. For others, it may be a steady stream of parenting items. Or baseball discussions.

Discovery is the middle ground. It’s things you weren’t looking for, but find interesting. Maybe Flickr Favorited pictures. An interesting tidbit from the world of science. An Inquisitr celebrity update.

Noise is the stuff you just don’t have the patience to put up with. It’s not anything you’re seeking, it’s annoying you that it’s even on your screen.

In this definition, there’s a fine line between discovery and noise. I’m argue that its the quantity of entries that determine whether something is noise or not. A few items creeping into your FriendFeed is probably all right for all but the hard core signalists. At some point though, when the volume of stuff you’re not seeking crosses a threshold, the entries become noise. You’re not getting enough of the stuff you’re seeking.

Everyone has their own threshold for discovery versus noise. This is the personalization required for noise control. Alexander van Elsas touches on this issue in a recent post:

It’s the noise problem (Try a search on “noise” here for example). How can we find the things that are really important from that huge pile of information floating around. That is partially why we have aggregation and filtering services. Each of them, using one algorithm or another, tries to compile a tiny subset of the universe and present that to its users. The question that remains is whether or not the right tiny space is presented.

Alexander strikes me as being closer to the signalist end of the information spectrum.

FriendFeed Rooms + Ranking Algorithm > Filters?

This brings me back to Kingsley’s point of view that ranking algorithms are optimal for noise control. Ranking algorithms are absolutely terrific. I love them. They provide a lot of benefits in a number of areas (e.g. Google Search).

I’m should also note FriendFeed’s Rooms as the other initiative for isolating topics and controlling noise.

Are they enough to control the noise? It’s hard to say yet. For Rooms to be effective, members are going to need to use them pretty frequently. That can happen over time, but it’s still dependent on the broadcasting member using them. There won’t be 100% compliance because:

  • I can’t perfectly predict what my subscribers will think is noise
  • Likes and Comments on something outside my usual programming put entries into my subscribers’ streams

The ranking algorithms will be interesting. Looking forward to seeing what gets rolled out. Knowing the FriendFeed gang, it’ll be good.

The difficult part is finding the middle ground between the hard core signalists and the discoverers, who like a fair amount of entries outside the stuff they seek. Neither group wants noise, but the threshold for the number of unseeked items varies greatly. My tolerance is pretty high, so I guess you’d call me a discoverer.

Balancing the desires of the signalists and the discoverers, and the varying thresholds of individuals will be the challenge. Let’s see what the ranking algorithms do.

I’m @bhc3 on Twitter.