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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!

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Hey Toluu Heads! Check Out the New Hover Boxes!

Toluu, everyone’s favorite blog discovery app, released a cool feature Wednesday morning. Hover boxes that show the last five posts for a blog:

Just put your cursor over any link to a blog, and the hover box appears. Anytime a blog is displayed in these places:

  • Profile
  • Matches
  • Feed Lists
  • Subscribers View

Discovery of interesting blogs just got that much easier. No need to click on the blog name and land on Toluu’s page for that blog. With a quick scan, you can determine your interest in the blog by reading the last five blog post titles. Founder Caleb Elston explains why this feature was rolled out:

We decided to build in this functionality when we found ourselves passing by feeds because we didn’t want to wait for the page to load or have to hit the back button if the feed wasn’t so interesting. Since we weren’t always willing to take a risk on a feed to see if it might be cool, we knew other users wouldn’t either.

And…the five blog posts listed are all hyperlinks that will take you directly to each individual blog post. My suggestion for Caleb – set the links to default as ‘open in new window’. I’d like to keep my Toluu window open so I can return to it.

Also, I think I see some FriendFeed inspiration for the new hover boxes…

As usual Caleb, really nice work on this feature. Both useful and usable.

If you haven’t tried Toluu, here are a couple posts that describe it:

If you need an invite, just leave your email in the comments below. I’ll shoot one out to you. And you can check out my Toluu page here.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Hey+Toluu+Heads!+Check+Out+the+New+Hover+Boxes!%22&public=1

Smart Social Media Marketing: Caleb Elston and Toluu

Interacting with bloggers called vital for business

Brice Wallace, Deseret News, June 7, 2008

Toluu released several new features on Wednesday. The features are cool, and are covered in another post on this blog. Which leads to the point of this post…

Caleb Elston did a masterful job of getting coverage for his fledging company Toluu. By himself, with no PR firm. How?

Caleb is a participant in social media. He’s established relationships and credibility with bloggers, and with others on FriendFeed and Twitter.

In a recent post, I asked Will Brands Figure Out FriendFeed? The idea is that rather than rely only on standard press releases and marketing campaigns, companies should look at engaging customers out in various social media, with a focus on FriendFeed. Establishing these deeper relationships pays dividends:

  • Reliable audience for updates
  • Viral distribution of company information
  • Customer advocates
  • Feedback from the market, with the ability to follow-up on questions/comments

Caleb has all of these advantages through his efforts in social media. How involved is he? On FriendFeed, he subscribes to 278 people, has 248 Comments and 244 Likes. On Twitter, he’s following 479  people and has 734 updates. In other words, he’s involved. Which is actually pretty amazing considering he has a day job on top of building out Toluu.

Yesterday, his involvement paid dividends. He reached out to bloggers the day before to let them know of an upcoming release for Toluu, and asked us if we wanted to cover it. Well, since I know him already, saying ‘yes’ was easy. He got eight different bloggers to write about the new release:

The combined Technorati Authority of those eight blogs is 872, which is like getting a top 5,000 blog to write about you. Many of the bloggers are active on FriendFeed, which combined with their existing subscribers, meant that a lot of people saw the news about the new features.

Caleb describes the payoff:

All I can say is wow. Yesterday was an amazing day for Toluu, you helped us shatter every metric we track. We had a record number of pageviews, visitors, signups, new feeds, connections made, invites requested, and time spent on the site. All I can say is thank you.

He even picked up technology celebrity Leo Laporte as a user. Said Leo, “I’m in dire need of a feed reset!”

Admittedly, as a small start-up with limited resources, this is all he could really do. He can’t crank up the PR, marketing and advertising machine.

But that doesn’t devalue the accomplishment. Caleb managed to get people interested in his company thanks to his active involvement in social media.

Big companies…are you listening?

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22Smart+Social+Media+Marketing%3A+Caleb+Elston+and+Toluu%22&public=1

Subscribe or Not? Toluu Just Got Better at Helping You Decide

A couple months ago, I had a chance to review Toluu, the blog recommendation site. The site is great, and has gotten really good uptake. In that review, I did write this:

I’d like to get a little more info about some of these blogs in a summary fashion, without having to click each one.

Well, Caleb Elston and team have delivered some nice new features that do just that. Here’s what is new at Toluu:

  • View the most popular posts from a blog
  • Who else has subscribed to the blog within the Toluu world
  • What other blogs those same subscribers have subscribed to recently
  • Posts now have datestamps
  • The contact page loads 5 times faster

The new features providing context around a blog are particularly interesting for me. Let’s look at those.

Toluu Before and After

Here’s a screen shot of the page for a blog before the updates. The most recent post for the blog is shown, without any date information.

Next, the same screen with the updates. Below, you’ll see new tabs for the blog: Recent, Popular, Subscribers. Also, note that the post for the blog now has timestamp information (“Yesterday”).


With the addition of the tabs, you now have quick access to more information about the blog.

Popular Posts = Better Insight into the Blog’s Best Stuff

As you’re checking out whether to subscribe to the blog, you click on the Popular link. This is pretty nice. The blog’s most popular recent posts are shown. At a glance, the user can see if the blogger’s top stuff is interesting. A good way to gauge what animates the blog.


According to Toluu founder Caleb Elston, the determination of what’s popular for a blog is “a combination of our own data mixed in with some data from AidRSS and soon a few more sources.”

The list shown for this blog is a pretty good indicator of popularity.

Subscribers = Who Else Likes this Blog?

This feature is really cool on a couple fronts. As a user deciding whether to subscribe to a blog or not, the list of subscribers provides a reference of sorts. Who feels like there’s enough “there” to warrant a subscription?


You can see what other blogs the subscribers have added as well. For example, I see that Corvida added Blogsessive. I checked it out, and decided to add it myself. A really nice way to leverage the filters of others in finding blogs you may like.

In fact, in terms of human filtering, you now have three ways in Toluu to handle that:

  • The algorithm-based matches to others
  • Your selected contacts’ additions to their feeds
  • What are the other feeds of people who subscribe to your blog

As a blogger, I also find this feature very nice. You may know your number of subscribers, but do you know who they are? Well, with Toluu, it’s pretty easy to see who some of them are.

Nice Job

These changes are a great step forward in helping you decide which blogs warrant your subscription. Better sense of the blog’s content. Better sense of the crowd that likes a particular blog.

My wishlist still includes better macro, summary recommendations for blogs. But all in due time. Hats off to Caleb and team for adding these excellent features.

Also – I invite you to check out my Toluu page: toluu.com/bhc3 If want an invite, just leave me a comment.

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22Subscribe+or+Not%3F+Toluu+Just+Got+Better+at+Helping+You+Decide%22&public=1

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.

Delicious and Diigo: Differ in What It Means to Be “Social”

Andy Brudtkuhlhas has a nice post, 6 Reasons Diigo is Better Than Delicious. In the post, one of the reasons he cites for Diigo’s being better is its social aspects:

Diigo has an extra level of social networking that Delicious does not provide – at least not in a usable manner. You can connect with people that have similar interests based on what you tag.

I’ve been playing with them a bit. Here’s an initial impression I have of how “social” works in the two bookmarking services:

  • Diigo uses content to find people
  • Delicious uses people to find content

Delicious, an original web 2.0 company, still has “user-generated” as its core raison d’être. Diigo has the later-stage web 2.0 philosophy of being a “social network”.

Diigo: Social Is as Social Does

Diigo has been built to find people based on common bookmark and tag interests. It has social network features throughout:

  1. Finding people on Diigo is much easier than on Delicious
  2. Diigo generates user matches based on tag and bookmark compatibility
  3. User profiles
  4. You can see who has visited your profile page
  5. You can comment on the bookmarks of others
  6. You can share bookmarks with specific users

Networking on Diigo Is Easier

A basic function – finding other users – is much easier on Diigo than on Delicious. The graphic below shows the results of a search for my name:

On Delicious, you have to know someone’s Delicious handle. On Diigo, you can use a person’s regular name. Diigo’s approach is more like that of today’s various social networks:

Social networks make finding users easy. So does Diigo. Delicious doesn’t.

Diigo Social Recommendations

Diigo attempts to match you to others based on common bookmarks and tags. As the graphic below shows, it’s not exactly Toluu-like in its matching.

Levels of compatibility at 2% and 3% don’t quite inspire clicks for further investigation. Social recommendations are a work-in-progress at Diigo. Delicious doesn’t do recommendations.

Diigo User Profiles

For each link, Diigo provides a user profile of everyone who bookmarked the link:

So when you check out others who bookmarked something you like, you can quickly determine if they are someone to whom you want to subscribe. Delicious also lets you look at someone’s activity, but you have to click on their handle to see their page. There’s no profile provided on the list of users who bookmarked a link.

Diigo Visitors Info, Commenting, Bookmark Sharing

I’ll skip the screen shots for these Diigo functions. But here’s how they foster social networking:

  • Who visited my profile? Potential matches. Also lets you know when your social network paid your bookmarks a visit.
  • Commenting. Commenting enables discussion with others. Socializing.
  • Bookmark sharing. You can call out specific users with whom to share a bookmark. Very social.

Delicious Has More of a Crowdsource Feel

Where Diigo is social, Delicious emphasizes the interests of all users. What are people finding interesting. That’s not to say it doesn’t have social network aspects. On Delicious, you can:

  • Add users to your network
  • View your network’s bookmarks
  • Become a ‘fan’ of someone

But Delicious pretty much stops there on the social aspects. The rest of Delicious is centered around bringing order to the huge volume of crowdsourced bookmarks.

Delicious: Who Bookmarked That Link When?

The new Delicious has a really cool timeline that shows who bookmarked a given link when:

That timeline is a thing of beauty. Users, dates, tags, notes. Where Diigo wants to get you socializing around a bookmark, Delicious wants to provide you with information about how a link fared with the public at large.

As mentioned above in the Diigo user profile section, Delicious doesn’t provide user profiles in this listing.

Wrapping It Up

The new Delicious continues its mission of organizing a massive number of user-generated bookmarks and tags. It looks cleaner, and I like the way information is presented. Information organized by an army of user librarians. “Social” in this context means your bookmarks and tags are exposed to others, and you can find related content based on what others are bookmarking and tagging. People are the basis for discovering content.

Diigo wants people to interact via common interests in content. It has a lot of social network hooks. “Social” in this context means establishing and building relationships with others. Content is the basis for finding people.

I’d love to hear your thoughts on the different approaches of Delicious and Diigo. And you can find me on both services:

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Delicious+and+Diigo%3A+Differ+in+What+It+Means+to+Be+%E2%80%9CSocial%E2%80%9D%22&public=1

What’s Your Blogging Style? Use FriendFeed Likes/Comments Ratio to Find Out

Julian Baldwin asked a question today on FriendFeed: “Roughly speaking, what is your comment to like ratio here on FriendFeed?” Based on the responses, a  lot of folks are doing more commenting than liking, but I suspect the responses aren’t totally representative. Still you can see a lot of emphasis on commenting.

Which made me wonder about turning this around a bit. Instead of looking at each person’s ratio of Likes to Comments, what could be gleaned from figuring that ratio out for a blog?

I selected several blogs, and totaled the number of Likes and the number of Comments for the last 30 posts of each blog. I then calculated the ratio of Likes to Comments, and mapped the bloggers to roughly one of four blogging styles:

  • Stir it up
  • Can we talk?
  • Observing the scene
  • Stuff you want to know

There are some adjustments and limitations related to this; they follow below. But first, the map of bloggers to blogging styles. To reiterate, the ratios you see below are calculated this way:

# Likes / # Comments = blogging style

So for instance, Dave Winer’s ratio is actually below 1.0. He gets more Comments than Likes. Here’s the map:

As I put this together, the analysis does seem to ring true from my perspective.

Here are the adjustments and limitations:

  • Some bloggers are really active at responding to comments on FriendFeed. This tended to drive their number of Comments up. For instance, Alexander van Elsas could put on a clinic in terms of engaging commenters on FriendFeed. I should be so good. So I gave the number of Comments a haircut for several bloggers.
    • Alexander van Elsas – 33% haircut
    • Myself – 25%
    • Mark Dykeman – 25%
    • J. Phil – 25%
    • Colin Walker – 25%
  • The analysis only applies to the main blog for each person (listed below)
    • No Toluu activity updates
    • No Qik videos
    • No side blogs that augment the main one
    • Etc.
  • Only the blogger’s own feed was used in this analysis. This is imperfect, as it does not include Likes and Comments for other ways thr blog post gets into FriendFeed:Google Reader shares, tweets, direct posts, del.icio.us, etc.
  • Some great new bloggers aren’t here, as they build out their blogs with posts.
  • The 30 blog posts per author only included entries with at least 1 Like or Comment.

And quickly, here are the links to the blogs used in the analysis:

What do you think? Does the Likes/Comments Ratio make sense as a blog style indicator?

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22What%E2%80%99s+Your+Blogging+Style%3F+Use+FriendFeed+Likes%2FComments+Ratio+to+Find+Out%22&public=1

Weekly Recap 061308: Social Media Exposure

Social media means exposure…exposure of your life…exposure to people interested in and knowledgeable about subjects you like…exposure to things that might offend you…exposure for your company

*****

Had fun this week with my post Nudity on FriendFeed: What Are Some Sensible Rules?…I wrote it for two reasons…(1) to get a temperature check from FriendFeed members as to where they stand with regard to nudity in their streams…(2) to point out that users have some control over their exposure to such things…

Michael Hocter, whose Flickr Favorites entry prompted me to write the post, reports that he gained a lot of new FriendFeed subscribers…and he’s sticking with the nudes (NSFW)…

I also learned that showing a topless model in your blog post will drive site visits better than anything…usually, my posts have a greater number of subscription views than site views, but this post was the opposite…a lot of click-throughs to the blog…

One concern…the word nudity in the post will get me some unwanted attention from odd spammers…thank goodness for Akismet

*****

Interesting development…FriendFeed now has a ‘block’ feature…as I write this, the FriendFeed guys haven’t posted anything about it yet to their blog…but here’s what the text says when you use the ‘block’ feature:

After blocking this user, you won’t see any of their posts or comments on FriendFeed, and they won’t see anything you post. If they’re subscribed to you, that subscription will be removed.

Here’s how Bret Taylor describes the philosophy of the feature: “Blocking is not a filtering mechanism, but an abuse prevention tool.”…this is going to come in handy…

****

NBC News’s Tim Russert passed away today, from a heart attack…I enjoy following politics, and when I lived in Washington D.C., I couldn’t get enough of it…Tim Russert served up outstanding questions, a respectful demeanor and a tenacious pursuit for answers to his questions…I also enjoyed his book Wisdom of Our Fathers: Lessons and Letters from Daughters and Sons

Amazing array of items related to Tim Russert on FriendFeed…blogs, direct posts, news articles, tweets, photos, videos…

*****

Jeremiah Owyang asks Does the President need to know how to use a Computer/Web?…NO!…there are so many things that go beyond our technology world, why would we stress this?…give me an authentic leader, who can surround himself with a talented team, who has positions with which I agree, and who can drive an agenda at home and abroad…computer user is pretty low on my list of requirements…

*****

How FriendFeed has altered one of my behaviors…I often share only three items at once in Google Reader…three is the maximum number of shares that display with titles in FriendFeed…do more than that, and you get two blog titles visible, all others relegated to the dreaded “[N] more” link…

*****

Caleb Elston released new features this week for his company Toluu…those are great, but I thought an equally cool story was how Caleb leveraged his blogger relations and presence on FriendFeed and Twitter to spread the word…

I added up the Technorati Authority of the eight blogs that covered the new features…the combined Authority of 872 is the equivalent of getting a Top 5000 blogger to write about you, but even better…those eight different posts were bouncing to the top of FriendFeed over and over for each blogger’s set of subscribers, meaning the exposure was not dependent on one blog post getting traction…something to think about for future marketing…

*****

If you haven’t yet, make sure you check out Louis Gray’s post this week about The Five Stages Of Early Adopter Behavior…my favorite is Stage #4 “Sense of Entitlement, Nitpicking and Reduced Use”…I’m not an early adopter type (I still have a mini-brick Sprint cell phone), but I’ll have to watch myself for these stages…

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22Weekly+Recap+061308%3A+Social+Media+Exposure%22&public=1

FriendFeed ‘Likes’ Compatibility Index

A favorite feature of FriendFeed is the Like. You get to indicate your interest in an item with a simple click of the Like button.

The act of applying a Like does two things:

  • Provides feedback to the content creator
  • Reveals what your interests are

It’s that second point that is interesting. Amazon.com matches you to other shoppers based on what you buy in order to provide recommendations. Toluu matches you with others based on common RSS feeds. Diigo matches you based on common bookmarks and tags.

How about matching people based on common FriendFeed Likes? Call it the FriendFeed Likes Compatibility Index.

Curious about this, I went to my Likes tab on FriendFeed. I went back to my 50 most recent Likes, and tallied the number of Likes by others. By doing this, I figured I’d see with whom I had the most in common.

The top 29 people are shown below – I put the cutoff at having 4 Likes in common. Some of these folks I know, others I really haven’t interacted with yet.

Here are my top matches in FriendFeed:

  1. Atul Arora (13 likes in common)
  2. Louis Gray (13)
  3. Mitchell Tsai (11)
  4. Shey (11)
  5. Robert Scoble (10)
  6. Thomas Hawk (9)
  7. Julian Baldwin ( 8 )
  8. Jason Kaneshiro ( 8 )
  9. Mark Trapp (7)
  10. Charlie Anzman (6)
  11. Mark Dykeman (6)
  12. Bearded Dave (5)
  13. Bwana McCall (5)
  14. Mack D. Male (5)
  15. Mike Fruchter (5)
  16. Phil Glockner (5)
  17. Alejandro S. (4)
  18. Andrew Badera (4)
  19. Anthony Farrior (4)
  20. Dobromir Hadzhiev (4)
  21. edythe (4)
  22. Kenichi Matsumoto (4)
  23. Marco (4)
  24. Nikpay (4)
  25. Rob Diana (4)
  26. Ruth Ferguson (4)
  27. Shawn L Morrissey (4)
  28. Susan Beebe (4)
  29. Timothy Neilen (4)

One small observation – I’m not in sync with a lot of women, am I? What’s up there? FriendFeed Is from Mars, Twitter Is from Venus?

Now what I need to do is to subscribe to those on this list that I haven’t yet. Also of note – there were 241 different people with whom I shared a Like in this analysis. Really great how FriendFeed lets you come into contact with a wide range of people.

Would be cool if a script could automate the FriendFeed Likes Compatibility Index…

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22FriendFeed+%27Likes%27+Compatibility+Index%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

Explosion of Blog Aggregators…How to Keep Up?

I don’t know about you, but I’ve seen the names of a number of aggregation sites out there. It’s a very popular space, and I have not really understood who they were or what made them tick. But my growing enjoyment of FriendFeed made me wonder about what these other sites are up to. So I put together a high level survey of several of them.

There’s a really long table below. Before that, a few notes are in order.

Selected apps: This is by no means an exhaustive list. For instance, I just got into Yokway today, but haven’t had a chance to try it out. I just came up with a list from the serendipitous finds I’ve had. I also focused on earlier stage companies – no Digg, del.icio.us or StumbleUpon.

How stuff gets in there: There are three way that blog posts and news articles are added to these aggregation sites:

  • Submit: Users add a specific web page to the site, often via a toolbar ‘add’ button.
  • RSS share: Google Reader lets you ‘share’ an item in your RSS feeds that you like, posting it to your publicly accessible ‘shared items’ page, which is tracked by an aggregation site
  • RSS feed: The aggregation site takes a feed of all posts from a blog or news site

What’s interesting: Every site has its own secret sauce for what makes it tick. I tried to find things that seemed to each site apart from others.

Experience: I rate the user experience of these sites based how much was required to use them effectively. In this earlier blog post, I describe examples of light and heavy user experiences. Generally, lighter is better, but heavy can be OK for really good, distinctive features.

The point of this chart: It’s not to praise or bury any of these apps. Just to put together a list of what’s out there. If you’re an information seeker, a writer or seeking social connections with like-minded people, then you should check out some of these sites.

After the chart, I include links to other blogs with more information, plus a few thoughts as well.

Quick thoughts in dot…dot…dot fashion:

Diigo’s people matching based on common bookmarks and tags is a really cool idea, it reminds me of Toluu‘s matching based on common blog subscriptions…LinkRiver and Reddit have a very similar philosophy, with Reddit deploying a lot more categorization than LinkRiver….ReadBurner and RSS Meme are also very similar…Shyftr may have a light experience, but I’ll admit I found the overall user experience confusing right now (they’re in beta, it will improve)…Twine’s automatically generated tags for different categories was really interesting, need to explore that more…no notes on FriendFeed, just click ‘FriendFeed’ in my tag cloud for information about it…I kind of like getting my daily Social Median emails with news updates…Blog Rize has a spare UI, but it is strangely compelling…luckily, none of my blog posts have received the ‘lame’ or ‘facts wrong’ ratings on Blog Rize…

Wrapping up, here are some blog posts to get you started on the various apps:

I may be posting about some these sites in the days to come.

*****

See this item on FriendFeed: http://friendfeed.com/e/9bdd0ad9-a377-f65d-6140-8dc4e835c6c3

You Can’t Win If You Don’t Play: A Blog Hits 50 Posts

WARNING: this is a navel gazing post. If don’t want to read this, go see what’s on Techmeme.

This blog just hit 50 posts, nearly three months after it started. That number actually crept up on me – hit me when I wasn’t looking.

I wanted to recount a few things of note over the past few months. Ideally entirely in Larry King dot-dot-dot format. But I tend to be more verbose. Anyway, let’s dig in, shall we?

Dot…Dot…Dot

I’m having a lot of fun, the little blog experiment has taken on its own life…getting blog subscribers, FriendFeed followers and Twitter followers means I don’t have to pimp my blog on other blogs as much anymore…that Louis Gray, well, whew boy…one thing I’ve learned, there are informal, unstructured social networks of bloggers…speaking of which, I need a better connection with Sarah Perez…my appreciation for uber blogger Robert Scoble has increased immensely: insightful, witty opinions that fire up readers…best feeling in the world is to put a new post up on the blog at midnight, go to sleep, wake up and see Gmail filled with notifications of new blog comments, Twitter and FriendFeed follows, links from other blogs…my social media consumption workflow: gmail, this blog, FriendFeed, Google Reader, Twitter, in that order…appearing on Techmeme, like getting a plum part on a Law & Order episode for an unknown actor…Techmeme founder Gabe Rivera’s Twitter page currently has a picture of lion eating a zebra, which makes me think, what’s Gabe’s story?…how long until I screw up and write something I shouldn’t?…my blog idea process is ad hoc, haphazard and based on serendipity – every day is a surprise…

Biggest Surprises

I titled this post “You Can’t Win If You Don’t Play” as a way of saying that you need to just participate in order to see the benefits. I could not have foreseen some of the following things that occurred when I started this blog.

LouisGrayCrunched. Louis Gray wrote a very nice post on April 7, 2008 that said this was a blog people should be reading. He did it after I wrote a post reviewing the Toluu service. His post put this little blog on the map for a lot of his readers, many of whom are here now as well. I can’t tell you how grateful I am for his ongoing support.

Proposal to Clean Up FriendFeed Clutter. FriendFeed co-founder Bret Taylor picked up on a post I wrote suggesting ways to better organize the updates in FriendFeed. He posted it to FriendFeed and a there was a really nice discussion there around the ideas.

Web 2.0 Jedi. This post has really surprised me. It was picked up by Digital Inspiration, based in India, which has a huge following (“the 40th most-favorited blog on the Internet”, according to Technorati). Many, many clicks from there, and that blog has been a gateway to bloggers around the world. A number of international blogs have included the graphic and linked to the original post.

Techmeme. Three posts made it onto Techmeme (here, here, here). Can’t believe it.

Social Media Identities. I love the discussion that occurred here. Included industry folks with whom I don’t normally connect.

Twitter Just Grows and Grows. This simple post turned out to be quite popular. It told me there’s a real interest out there in Twitter, and information is harder to come by than I realized. TechCrunch later ran a post about the “real Twitter usage numbers”.

‘Peanut Butter’ searches. I continue to be haunted by the mysterious ‘peanut butter’ search visitors. People searching for ‘peanut butter’ continue to be my biggest source of visitors. Who are you? What search engine are you using (it’s not Google)? What makes you click through? I may never know the answer to these questions.

My 5 Favorite Posts of the Blog

This is like picking your favorite child, but here they are:

  1. FriendFeed RSS Is a Fantastic Discovery Tool
  2. Becoming a Web 2.0 Jedi
  3. Farewell, Pay By Touch, Farewell
  4. Proposal to Clean Up the FriendFeed Clutter
  5. Innovation Requires Conversations, Gestation, Pruning

Best Posts for Comments

These posts were most active in the comments section (including my comments):

  1. Becoming a Web 2.0 Jedi: 20 comments
  2. Social Media Identity: Personal vs. Professional: 16 comments
  3. The Best Blogs You’re Not Reading? Toluu Knows: 11 comments

Most Viewed Posts

  1. How to Write a Farewell Email to Your Co-Workers
  2. Early Adopters: Attention Is Migrating to FriendFeed
  3. Pay By Touch and the Peanut Butter Manifesto
  4. Becoming a Web 2.0 Jedi
  5. Farewell, Pay By Touch, Farewell

Top Referring Websites

My blog really isn’t part of the StumbleUpon and Digg worlds. FriendFeed has become my top day-in, day-out referral site.

  1. Techmeme
  2. FriendFeed
  3. Google Reader
  4. louisgray.com
  5. wordpress.com
  6. Digital Inspiration
  7. Twitter
  8. Stumbleupon

Top Search Terms

Peanut butter…peanut butter…peanut butter! Aaagh!

  1. peanut butter (several variations)
  2. farewell email (many, many variations)
  3. pay by touch
  4. peanut (basically a peanut butter variation)
  5. friendfeed rss
  6. blogs
  7. facebook
  8. reasons for fatigue

And that concludes the navel gazing. If you made it this far, thanks for reading.

*****

See this item on FriendFeed: http://friendfeed.com/e/9c2030a5-c02e-dd79-f274-caf58e1af8e8