Toluu Rolls Out Tagging {cool} {powerful} {discovery} {easy}

Toluu, everyone’s favorite blog recommendation application, has released a powerful new feature: tagging.

Tagging is a ubiquitous element of Web 2.0. As content creators and consumers add tags, everyone benefits. Things are easy to find, and there’s fun in clicking those tags – you never know what you’ll discover. I’m also a fan of the idea that tagging illuminates someone’s interests. Know someone’s tags, know their interests. A look to the right side of this blog shows the areas that I like to cover. As Toluu founder Caleb Elston has previously noted:

Tagging is super powerful. A few simple words can bring a ton of order and new usefulness.

And Caleb has followed up on that observation with powerful new tagging features in Toluu. Here is what’s new:

  • Tag Tab: Clickable tab for each blog page in Toluu, with several tag related features
  • Explore by Tag: every tag is clickable, leading to a list of related blogs
  • Inline Tagging: Instantly tag a blog right from a list of blogs
  • Users’ Tags: See the tags that a user has applied within the Toluu application

All in all, the features bring a new level of sophistication and community-generated perspective to the blog recommendations. Let’s check ’em out.

Tag Tab

The tag tab is chock full of information for every blog listed in the Toluu system. Here’s a screen shot for this blog:

Tagging: The top of the Tag Tab has an entry box for entering new tags. A couple of notes:

  • Tagging is multiple word, comma separated. Yes!
  • Tags are auto-suggested, based on tags you’ve used before. This is a great feature. It makes it easier to add tags, and enforces consistency, which is so important in tagging.

My Tags: These are the tags you have already applied to a given blog.

Top Tags: These are the most popular tags applied by others to a given blog.

Related Blogs: Each Tag Tab includes a list of related blogs. These are blogs that share similar tags to the ones applied to a given blog. This makes discovering a bunch of blogs with a specific area of focus very easy.

Follow the Bouncing Tag

In fact, it gets even easier to find blogs with a specific focus. Just follow a tag where it takes you.

Notice the nice distinction above? You can see blogs with specific tags applied by anyone in the system. Or you can take a deeper dive, and see what someone you trust has tagged.

Sorting: There are four different ways to sort the list of blogs by tag:

  1. Popular = blogs are ranked by the number of times they received a particular tag
  2. Recent = sort by how recently a specific tag was applied to a blog
  3. Subscribers = sort by the number of Toluu subscribers to a blog
  4. A-Z = alphabetical

Inline Tagging

To make tagging easy and pervasive, inline tagging is supported.

As you look at your list of blogs, you can quickly tag them. I like this because it makes the tagging process fast and easy. I don’t have to go to each individual blog’s page inside Toluu to add tags.

User Profiles Now Have a Tag Story

All this tagging by users has another benefit. You can quickly see what someone is all about when you visit their profile in the Toluu system.

This is great. Toluu isn’t a full-fledged social network, but you can use it to find like-minded people. From these like-minded people, you can discover other blogs of interest.

The tags of a user are essentially a form of self-identification. Like declaring what political affiliation you have, or saying where you work. This at-a-glance insight into someone’s interests is a great way to figure out new people to follow inside Toluu.

Are You Toluu-ing Yet?

Caleb and his team have done a really great job with this new functionality. A lot of attention was paid to ease of use, and the subtleties of information discovery. He has built in the notion of discovery via the collective wisdom of crowds, or discovery via trusted information filters.

Toluu continues to innovate. Click here to see all posts tagged ‘toluu’ on this blog. It’s an impressive list of activity.

If you’re on Toluu, follow me at http://www.toluu.com/bhc3. I’ll follow back. And if you’re not yet on Toluu, I’m happy to email you an invite. Just leave a comment.

Nice job Caleb!

Made the Switch: FriendFeed Now My Homepage

In recent weeks, I’ve noticed my behavior has changed when I fire up the PC in the morning. My Yahoo has been my home page forever. I love the portal approach, with everything I like easily visible and accessible with a click.

But as soon as My Yahoo loaded, I quickly clicked over to FriendFeed. I really didn’t read much of what was displayed on My Yahoo.

I can be pretty loyal to apps and companies I like. I was doing this with Yahoo, despite the change in my behavior. Finally though, I realized that staying loyal and delivering a page view to Yahoo wasn’t really getting me anything.

I switched to FriendFeed.

My Top 5 Reasons for Making the Switch:

  1. Content that is filtered by my network on FriendFeed has more value to me than what I see on My Yahoo
  2. My interest in all the content I see on My Yahoo is only fleeting, but a portal demands that it’s always there (e.g. stock quotes)
  3. Hitting Refresh on My Yahoo only brings up the same stories. FriendFeed has the most amazing river of new stuff.
  4. My Yahoo doesn’t provide some of the content I find most interesting = tweets, blog posts, articles directly posted, comments, Flickr Favorites by people I trust (note the Flickr irony…)
  5. My Yahoo takes too long to load

I know I can control the portal experience by adding/deleting content. But that’s a pretty heavy process to me. And it doesn’t really come close to the constant stream of interesting new content that FriendFeed delivers.

I don’t mind the ads so much, but that big fat Classmates.com ad sure does take up a lot of real estate. I expect when Friendfeed includes ads, they’ll be more subtle like Google AdWords.

Biggest concern? I’ll fail to check my Yahoo Mail without the link I have on the My Yahoo page. A number of people still use that email to stay in touch.

If Yahoo can get clever and revive itself, I might make it my home page again. But for now, it’s FriendFeed.

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See this post on FriendFeed: http://friendfeed.com/search?q=%22Made+the+Switch%3A+FriendFeed+Now+My+Homepage%22&public=1

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.

*****

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.

*****

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…

*****

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…

*****

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)…

*****

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

WordPress Content Recommendations: Off to a Good Start

I love recommendations. Well done, they make my life easier and provide a great source for learning things I didn’t know. So I’m pretty excited about a new feature rolled out by WordPress.com, “possibly related posts”, on April 26, 2008.

At the bottom of blog posts on wordpress.com, you’ll see a list of several blogs under the heading, “Possibly related posts: (automatically generated)”. These are posts which should have some relation to the blog post you just read. WordPress is working with Sphere to deliver these recommendations.

There’s an priority ranking to the recommendations:

  1. Similar posts on the same blog
  2. Similar posts from around wordpress.com
  3. Articles, blog posts from elsewhere on the Web

Two areas are of interest here: (i) what recommendations appear on your blog; (ii) what other blogs are showing your posts shown as ‘possibly related’.

Recommendations That Appear on Your Blog

I surveyed five of my blog posts to see what were listed as possibly related posts. They’re shown below, along with a rating of ‘yes’ for related, ‘no’ for not related, ‘sorta’ for posts that might appeal to some readers of the blog post.

I. Ten FriendFeed Visitors Beats 1,000 StumbleUpons Any Day (link)

  • Wired blog: FriendFeed Offers Developers the Key to Build Custom Social Apps (link): no
  • New York Times: Friends May Be the Best Guide Through the Noise (link): yes

II. You Can’t Win If You Don’t Play: A Blog Hits 50 Posts (link)

  • This blog: When Your Blog Is LouisGrayCrunched… (link): yes
  • A wp.com blog: asylum street spankers, and a word about hits (link): sorta
  • CBS Sportsline: Major League Baseball (link): no

III. How Do Solo Bloggers Break into the Techmeme !00? (link)

  • A wp.com blog: break (link): sorta
  • A wp.com blog: Ichimonji No Kata – Raiko No Kata – Kukishin Dakentaijutsu (link): no
  • Scobleizer: New PR Trend: Anti-Gaming TechMeme? (link): yes

IV. The Best Blogs You’re Not Reading? Toluu Knows (link)

  • A wp.com blog: ‘A Fistful of Euros’ awards (link): yes
  • A wp.com: The demise of letter writing: oh, really? (link): yes
  • A wp.com: Reading blogs simply (link): no

V. How to Write a Farewell Email to Your Co-Workers (link)

  • A wp.com blog: How To Write Emails People Will Actually Read (link): yes
  • A wp.com: Email Etiquette (link): yes
  • A wp.com blog: Getting Better Results from your Email Marketing (link): no

The recommendations are off to a decent start. “Related” is a subjective measure, and my ratings above may not match what another reader would think.

How about comparing the WordPress recommendations to other sites? Here’s what Kleiner Perkins-backed startup Aggregate Knowledge’s discovery algorithm currently shows on the Washington Post story, “Failed Yahoo Talks Leave Google on Top“:

Only one of four are related to the Yahoo – Google story. Admittedly, Aggregate Knowledge doesn’t tout itself as a ‘related articles’ service, but their list of other articles should be viewed in this context: “Will people click on those links?”

And here’s what the New York Times shows as “Related Articles” for the article “Friends May Be the Best Guide Through the Noise“, which discussed lifestream companies FriendFeed, Iminta and others:

None of the ‘related articles’ relate to the story.

Recommendations for Your Blog that Appear Elsewhere

What’s interesting here is that you, as a blogger, can see what other blogs have similar subject matter as you. Oh, and the possibility of increased traffic doesn’t hurt.

I’ve really only seen clicks to this blog on ‘possibly related’ recommendations from two sites (with links to posts that include links back to this blog):

  • Scobleizer.com (link)
  • Alexander van Elsa’s Weblog (link)

Neither of those is a surprise. Both have good posts related to social media and Web 2.0, subjects which are covered as well. The ‘possibly related posts’ from this blog shown there are relevant to the posts on which they appear.

Final Thoughts

I’m a fan of this feature, which is still in its early days. It does have its detractors though. Here are a couple comments posted on wordpress.com about the feature:

I actually hate the randomness of this, even though you’re using an engine to try to find related material. Here’s why this is a horrible bad idea, and really, you should turn it OFF everyone’s blog unless they specifically ask for it: If I want random, unvetted links on a topic, I’ll google it. The REASON why blogs are a great medium is one of TRUSTED information. If I know a blogger is smart, savvy, well connected, and honest, I will trust THEIR opinions, and look to what links THEY supply. Making these robot-choices LOOK like they are endorsed by the blogger is where this really falls down, and makes me want to shut it off immediately and everywhere. It is so unfortunate that this is on by default. I will recommend to everyone that they shut off this feature. This is so anti-blogging, it’s not funny, and in fact sad coming from a trusted blogging platform. I bet if you took this issue to serious bloggers first, they would have chimed in overwhelmingly in the negative camp.

Morriss Partee

What it seems to be designed for is to keep the readers IN wordpress, which is understandably your goal. What it PROBABLY will do for individual bloggers is take the reader away from his or her blog into someone else’s blog within wordpress, a dubious result in my way of thinking. But what do I know?

Alice

Count me as a fan, and I hope they continue to iterate through improvements to the recommendations. I fundamentally disagree with Morriss Partee. Blogging is about conversations, even if they go elsewhere. If my blog post piqued someone’s interest and they click to another blog, that’s fine by me. I’d rather the reader have a good time than try to trap him onto my blog.

Go WordPress, go!

*****

See this item on FriendFeed: http://friendfeed.com/e/7a1528d4-96c3-40ea-f5c3-6493372fa956

FriendFeed Tags Make Your Stuff Findable

A theme I come back to repeatedly here is that FriendFeed will be a terrific platform for research and discovery. In fact, for this purpose, FriendFeed gets better the more people use it. That’s a contrast from the information overload meme that has emerged, in which too many friend updates overwhelm people.

Another way to put it: “Research” FriendFeed versus “Friends’ Updates” FriendFeed.

A good point of comparison for Research FriendFeed is Google. Google is the first stop for most people when they want to find information on something.

A key difference between FriendFeed and Google is that Google indexes all the content on each page. A Google search will go deep into a web page’s content. FriendFeed has only limited information in each update:

  • Blog or article title (blog post, del.icio.us, Google Reader, Reddit, etc.)
  • 140-character message from Twitter
  • Name of the Flickr photo
  • Etc.

This puts a lot of pressure on the title of the article to well-represent its content. Many times it does. But more often than not, the article is richer in information than the title can convey. Also, contorting your writing – including the title – to maximize search effectiveness is just a bad move. Bad for writing, bad for reading, bad for authenticity.

These two dynamics – lack of full content, incomplete information in the title – call for innovation within the FriendFeed world.

Where will that innovation be? FriendFeed comments.

Comments are free-form, and easy to add. And they’re part of the FriendFeed search index. If a good conversation erupts around an activity feed, those comments can be helpful for searches. But the conversation may not hit the mark either. And the majority of updates do not have a rich conversation around them.

As the author of a blog post, you may want to take a more active role in whether your content shows up in searches on selected terms. May I suggest tagging as an answer here?

In a comment, simply type ‘tag:’, followed by any tags you’d normally use. Using the “tag” prefix lets everyone know that it’s not a conversational comment. It’s a metadata comment.

Here’s an example. I recently wrote a post called, “Innovation Requires Conversations, Gestation, Pruning“. The article can apply to any general environment where innovation occurs. However, the focus of the post is really on employees inside companies. Internal blogs can be powerful centers for incubating innovation.

The post has a strong Enterprise 2.0 theme. Yet the title of the post doesn’t tell you that. So I went into the comments section for the FriendFeed blog post update, and added this:

tag: enterprise 2.0

Sure enough, the post now shows up in a search for ‘enterprise 2.0’. It also showed up in my RSS feed of ‘enterprise 2.0′ updates from FriendFeed.

Not everyone will bother with tags, of course. But tags are mighty useful things. If you create content and want to make sure it’s findable, tags are a good strategy to make sure it’s “findable”.

And this idea extends to adding your own tags to others’ content. You could create your own tags to associate to content you like and want to track.

And tags help others understand the context of the content.

This post may be a bit early. But it is something to think about in a future where FriendFeed is the third leg of research: Google, Wikipedia, FriendFeed.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22FriendFeed+Tags+Make+Your+Stuff+Findable%22&who=everyone

The Best Blogs You’re Not Reading? Toluu Knows

Toluu has entered the ever-growing recommendation space with something different: blog recommendations. And the service does a good job of finding blogs you’ll like.

I love the RSS experience of reading various blogs, loading up my reader with a lot of them and checking updates several times a day. So I was happy to have the chance to try this out. The service is new, launching in mid or late March. Louis Gray has a good post detailing its initial launch. Here’s a description of how it works from the Toluu site:

  • After joining, you will be prompted to import your feeds. We have many methods of importing your feeds such as OPML import, URL input, and a nifty bookmarklet.
  • Toluu will do some crazy math to find others in the system who have similar tastes as you.

One thing founder Caleb stressed on his blog: “Toluu is not another social network. I repeat Toluu is not another social network.”

So with that intro, let’s look at the user experience and how Toluu rates versus competitors. First, a brief discussion of recommendations.

Quick Note on Recommendations

The recommendations space is a hot area right now. For instance, Loomia, which recommends web content based on what your friends read, just raised $5 million. Amazon.com has been a real pioneer here with its “customers who bought this item also bought…” recommendations.

Ideally, recommendations are exactly matched to your interests. That’s pretty much impossible, but recommendations engines will employ proxies to get a bunch of recommendations that are close to your interests. And hopefully one or more click with you.

There are myriad ways to approximate your interests, and the world of recommendation engines is full of different methodologies. The key thing for most of them is (i) the amount and quality of information about your preferences, and (ii) the amount of population data available to build out recommendations. Toluu uses your OPML file of feeds, which is a very good source of data about your preferences. And Toluu improves as more people participate.

Finally, I’d want a recommendation service to mix highly popular items that I may be missing, as well as less popular items that are relevant to me. That latter category is the real jewel of a recommendation engine, and its the hardest to get right.

Toluu’s Organizing Principle: Match Percentage

Toluu’s primary organizing basis is its Match %. As Caleb mentioned above, this is their “crazy math” secret sauce. After you log in, you click on matches. A list of 5 people are displayed, sorted according to the Match %. The first 5 people you see are your highest matches. Each subsequent page shows the next 5 highest rated people. Each person has 5 feeds listed beside them. These “feeds you might like” are the top 5 recommendations per person.

I had 60 people in my list of matches. My highest match was at 91%. The bottom of the list was guy with whom I matched at 31%.

As I looked through the people that I matched, I noticed a trend. The best Match %’s were with people who had fewer blogs. The lower Match %’s seemed to be with people that had large numbers of blogs. I pulled together some numbers for 30 people to see if this was true. My top 10 matches, 10 people that fell just below the 50% Match %, and my bottom 10 matches. I then graphed it:


Sure enough, the higher the number of feeds for a given user (red line), the lower the Match % (blue line). I’m not quite sure what to make of that. It may be an outcome of the math – the match percentage is lower just because a user has so many feeds there’s no way to match. Or maybe I don’t match up well with the hard-core RSS addicts. I dunno.

One effect is that people who go deeper in their blog interests will fall lower in my matches. Assuming users don’t go too far down in viewing their matches, this could reduce the chance for finding those golden nuggets of less popular, but valuable blogs.

Top Toluu Recommendations Can Be Limited

I cruised through my people matches, and read the 5 “feeds you might like” for each one. There is a high degree of commonality on the recommendations. The 5 recommendations seem to use popularity as an primary input. And that makes sense. You’re providing a service, and popularity means somethings been deemed worthy by the public at large. Start with that!

Again, I looked at the top 5 recommendations for the 30 people I analyzed above. That meant I was looking at my top matches, my mid-tier matches, and my lowest matches.

There wasn’t a lot of variation in the top 5 recommendations for people in the different groups. Micro Persuasion, Engadget, Lifehacker, a couple Google company blogs and Boing Boing consistently showed up, regardless of the Match %.

This narrowness in the recommendations was something that Allen Stern at CenterNetworks wrote about. If you see a recommendation once, you’ll tend to see it repeatedly.

The Rubber Meets the Road: Toluu vs. Google Reader vs. NewsGator

So all that’s well and good. But how does the service perform? I decided to see how Toluu worked relative to two big established market players: Google Reader and NewsGator.

Google Reader has a Discover function. Here’s how it’s described: “Recommendations for new feeds are generated by comparing your interests with the feeds of users similar to you.” Sounds like Toluu, doesn’t it?

NewsGator has a Recommended for Me function: “NewsGator has analyzed your current subscriptions and post ratings, and recommended these new feeds for you.” Doesn’t say how that’s done.

I compared the top dozen recommendations for each of the three services. To assemble my top 12 for Toluu, I calculated the number of times the different blogs appeared in the 30 people I analyzed above. For instance, the blog Micro Persuasion appeared in 19 of the 30 matched users, making it #1. The table below shows those top 12 for each service:

One thing that immediately was apparent. No blog appeared more than once! Three different sets of recommendations and no overlap among Toluu, Google and NewsGator. Incredible!

I then checked out the 36 different sites. After a quick scan of each one, I decided whether it was one I would add to my RSS feeds. Those are highlighted in yellow above. NewsGator’s recommendations fell flat with me. They were too hard-core tech. Several had blog posts with lines of code on them.

Google Reader’s recommendations were the most relevant for me, with 5 that I liked. I subscribe to a number of Enterprise 2.0 blogs, so blogs like Intranet Benchmarking Forum and Portals and KM were good.

But Toluu did well here. The crowd was right – I like Micro Persuasion. Webware.com and Web Worker Daily are also interesting. There are a lot of Google blogs that show up in the recommendations. Maybe a bunch of Google employees are trying out the service?

More people joining Toluu will probably improve this some. At least push the Google blogs off the top recommendations. But there will be some reinforcing behavior as people join. Sites like Engadget and Lifehacker have large followings, and I’d expect a number of new folks joining Toluu to have those already.

Serendipity: Looking at My Top Matches’ Other Blogs

For each person in your match list, you see all the blogs they have that you don’t. It’s here where some of those golden nuggets, and even better known blogs, can be found. It takes work. You need to click each person, and then click each blog. There’s a limit to how much of this I wanted to do.

So I only looked at the feeds of my top 3 matches. And, I did find more blogs I’m going to add to my Google Reader:

  • Marshall Kirkpatrick
  • Adam Ostrow
  • BubbleGeneration
  • SocialTimes.com
  • mathewingram.com/work

Toluu Assessment = These Guys Are Doing It Right

I picked up 8 new blogs to follow courtesy of Toluu. That’s no small accomplishment. And considering they’re just getting underway and don’t have a ton of users yet, they compete quite well against Google.

I haven’t touched on other features of Toluu has. You can favorite a blog in your collection. I assume this helps the matching algorithm? You can track the activities of others to see what blogs and contacts they’re adding. But remember…this is not a social network!!!

Things I’d Like to See

I’d like to have an easier experience seeing the feeds for my top matches. Since there’s such a commonality in the top 5 for each of them, it would help me discover other blogs if I could see several of my matches’ unique blogs at once.

Show the top ten blogs recommended for me based on my top 10 matches. Criteria = frequency of a blog’s recommendations, with overall popularity as a tie breaker.

I’d like to get a little more info about some of these blogs in a summary fashion, without having to click each one. Maybe the headlines for the most recent 3 posts, or top tags of the blog?

But all in all, a very nice start for Toluu. Thumbs up here. Now I’ve got to go scan my RSS feeds.

FriendFeed RSS Is a Fantastic Discovery Tool

FriendFeed will be one of the best research & discovery tools there is. I don’t say that lightly. Here’s why.

Jeremiah Owyang has a post up today, My Essential Twitter Tools. He lists seven things he uses to get the most out of Twitter. Among the items are these:

  • Search: Use Tweetscan to see who’s talking about you, your brand, or a topic you’re interested in. For example, I may not just search on “jowyang” but also on “owyang” as some don’t use the full name.
  • Aggregation: Friendfeed puts all of our RSS content onto one page, making it easy to see from one glance (rather than going to different properties) and you can even reply from friendfeed to different tools. It’s smarter to organize around people, rather than tools.

Tweetscan is a great resource for finding out information on a topic. You see what others are talking about and passing along for a given topic.

Well, FriendFeed is even better. On FriendFeed, people share their Twitter posts, the same content that Tweetscan searches. But they share many other application there as well.

  • Micro posts: Twitter, Jaiku, Pownce, Google Talk,
  • Websites, blogs: new blog posts, StumbleUpon, shared items on Google Reader, del.icio.us, ma.gnolia, Digg, Reddit
  • Presentations: Slideshare
  • And lots of other sources

All of these content sources are searchable. And they all have an aspect lacking in many search and discovery mechanisms: human filtering.

When someone takes the trouble to save or distribute content, that content has already passed an initial test. Does it have value to someone? If you save something to del.icio.us, that is your endorsement of its value. Add it to LinkRiver? Means you found the web page interesting. Sharing a blog post on Google Reader means the blog post held value. Recommend a book on Goodread? You get the picture.

The conversations that are captured are also incredibly valuable. They give insight into people’s thinking around a subject. They hold data that is useful. Many times, the micro posts include a reference to content that someone found valuable, even if that person didn’t bother to bookmark it to del.icio.us or share it on their Google Reader.

The implicit endorsements of content – via different services or conversations – are a tremendous benefit to someone doing research.

There’s also plenty of original source content that’s findable. Slideshare presentations. New blog posts. Videos. Photos.

Finally, from the recommendations, conversations and content, you can find people who share your interests. You may want to do the social thing and add them to your FriendFeed network. Or you can check out what other sites, content and conversations they have in their FriendFeed to potentially find other useful information. Heck, even reach out to the person to discuss a subject.

Adding RSS to this whole thing really powers it. You don’t have to go to the FriendFeed site to do a search. You can have new content delivered to your RSS feeder.

RSS? FriendFeed doesn’t have RSS?

Mark Krynsky over at Lifestream Blog has a wonderful hack that turns FriendFeed search results into an RSS feed. Click here to go his post.

I won’t stop using Google to search for a subject. But for leveraging the human filtering, I’ll use FriendFeed search. And for ongoing knowledge discovery, even when I’m not actively searching for a subject, I’ll use FriendFeed search RSS.

What do you think? Will FriendFeed become a primary research & discovery tool?

I’m @bhc3 on Twitter.