Who Is Your Information Filter?

This comment by Michael C. Harris on FriendFeed the other day caught my eye:

Heaps of fantastic shares from unknowns get almost completely ignored and yet Scoble shares “Scoble” and gets 50 comments

Michael is hitting on something very important. In FriendFeed, not all shared items are created equal. I’ve noticed some people are really good at getting people to click through on a shared item and start a conversation.

I think of these people as the new Information Filters. They have a knack for getting their subscribers to check out stuff they find interesting. More so than your average social media user.

Over time, a logical outcome would be this: as the Information Filters share information with their subscribers, click-throughs and comments occur on that content. Which attracts new people into the discussion. Who then subscribe to the Information Filter. Which increases the click-throughs and comments. Repeat…

Good Information Filters can find themselves with a lot of power to direct traffic, and subtly influence what others take in when it comes to information. This isn’t without precedent. Television and the web are prior examples of this.

Migration of News Consumption Habits

Both television and the web have seen changes in the way people get their news. In both TV and the web, the changes are based on the strength of someone’s personality and judgment as to what the audience wants:

In 2004, CNN reported a Pew Research Center survey of news viewing habits. The survey found that 21% of people aged 18 – 29 got their news on the presidential election from Jon Stewart and Saturday Night Live. A follow-up report “Where Americans Go for News” by Pew also noted:

During these late night hours, many young people are tuning into comedy shows such as David Letterman and Jay Leno. Those under age 30 are among the most likely to watch these types of shows 17% watch Leno or Letterman regularly, compared with 8% of 30-49 year-olds and 12% of those age 50 and older.

What do Jon Stewart, David Letterman and Jay Leno offer that the traditional news broadcasts don’t? Humor, obviously. They also get to pick the most interesting news items for their shows. NBC News anchor Brian Williams noted the obligation of professional news organizations to offer news that likely doesn’t interest most audiences:

Some people call it ‘eat your peas’ journalism because it has to include everything that’s good for you to know to be a good citizen of the world. We put it out there.

In this comment, you see the larger societal obligation felt by the mainstream news media. They cover everything, even the stuff you don’t care for. There’s a tension between ensuring people get a full range of information about our multi-faceted world, and what people are willing to pay attention to.

The web has undergone a similar change in reading habits. Matt Drudge’s Drudge Report has eclipsed traditional news outlets in terms of influence. From The Telegraph’s article Matt Drudge: world’s most powerful journalist:

So much internet traffic can be directed to an item linked to by Drudge that unprepared websites have been known to collapse under the strain.

For politicians, the effect is akin to a needle injecting information into the media bloodstream. A positive story can give a shot of adrenaline to a flagging campaign. More commonly, negative information can be like a dose of poison being administered.

Drudge rose to prominence when he famously put the Monica Lewinsky story in play. Since then, his traffic has grown enormously. It’s not just about that one scoop. Drudge has a good sense about what is newsworthy. From the Washington Post blog The Fix:

The second major reason for Drudge’s influence, according to the Fix’s informal poll of Drudge-ologists is his ability to sniff out a potentially big story when others — including reporters — miss it at first glance.

“He can identify what’s a big deal even when the reporters who actually cover and report on an event don’t realize what they have,” said one GOP strategist granted anonymity to speak candidly. “He scoops reporters’ scoops.”

What do Jon Stewart, David Letterman, Jay Leno and Matt Drudge have in common?

  • They don’t actually find and report news (for the most part)
  • They only present what they find interesting
  • They have shrewd judgment as to what audiences will like
  • Their personalities are part of their effectiveness as news filters – people trust them

Each of these guys have emerged as a key Information Filter.  New social media platforms, such as FriendFeed, are starting to see the emergence of their own Information Filters.

You Are Who You Follow

This is something Robert Scoble emphasizes: you define yourself by who you follow. Early FriendFeed employee Kevin Fox described the general role of your friends on FriendFeed:

The nature of FriendFeed is that you start to think that the world is like you, because your friends shape your FF world. I think the FF world is full of Obama supporters, and other people thing it’s full of Twitterers. Pick your friends wisely because they define your FF.

In an equal world, information shared by any of your friends will merit click-throughs and discussion. But the practical reality is that some people will be more “equal” than others in terms of driving the discussion agenda. There are two highly correlated components to that:

  • Number of subscribers
  • Reputation for identifying what is interesting

The sheer number of subscribers make some people Information Filters. The big power users on Twitter: Leo Laporte, Dave Winer, Robert Scoble, Jason Calacanis, etc. These guys really drive discussions around ideas, opinions and news. If you subscribe, you can’t help but be overwhelmed by the discussions they can kick off.

The reputation for finding interesting stuff is a little harder. Like Matt Drudge and Jon Stewart, you need to have a sense for what people want to know and find interesting. Some people are naturals at this, but I think anyone can learn how to identify interesting stuff.

Louis Gray is a really good Information Filter. Out of curiosity, I took at look at the last 30 Google Reader shares he put into FriendFeed. And I compared them to my last 30. I wanted to analyze the interaction around them: Likes, comments.

The chart to the right graphs the total Likes and comments for the 30 Google Reader shares of each of us. Louis is clearly good at putting things out there and having people discuss them. You’ll see the Likes and comments on his shares are double mine.

I consider Louis to be one of my Information Filters. He’s great at identifying the good stuff. And he takes this role seriously. He wrote a post Roll Your Own Blog Leaderboard with Google Reader Trends, in which he identifies the blogs he’s sharing most often.

The Effects of Our Information Filters

NBC News’ Brian Williams had this to say in response to the increasing application of personal filters to news:

Do you have a problem with people personalizing the news vs. you saying ‘these are the top stories’? Is there a danger in that if you give people too much personalization?

Williams: That’s for others to decide. I will say that if you’re using a filter, if you wake up in the morning and you have loaded up your computer, in other words to say, ‘Foreign news totally bums me out, this Iraq thing, it just ruins my day. Keep it away from me.’ Is that what [James] Madison had in mind, do you think? Is that what [John] Adams and [Ben] Franklin and [Thomas] Jefferson had in mind? Did they expect a little more informed electorate, to quote Mr. Jefferson? Did they expect a little more from us as citizens? I can’t judge people.

Democracy, on the other hand, looking at the argument, it’s their right [to filter]. I’m a lover of news and information, I’m a lover of American history, it’s my hobby. So if I had my druthers… Some people call it ‘eat your peas’ journalism because it has to include everything that’s good for you to know to be a good citizen of the world. We put it out there.

I can’t start programming the ‘NBC Nightly News’ with just the news that doesn’t bum people out. Just the news they want to see and hear. But I can’t stop someone from using filters, from using pay-as-you-go technology to get what they want. I will probably have my own opinion in a couple years about what we’ve become as a society as a result of if we stop getting the news that’s at all negative.

There’s a similar concern about over-reliance on our Information Filters in social media. That it becomes too easy to rely on what they find, and put in front of us. Robert Scoble asked a question that touched on this recently:

Hmm, how come you all like commenting on Google Reader Shared Items here in FriendFeed but you all do so little Google Reader reading yourselves?

Check it out for a good discussion around the merits of using FriendFeed exclusively for reading new blog posts.

Choose Your Information Filters Carefully

Brian Williams alluded to the “eat your peas” element of being an informed citizen. That is, take in information even when it doesn’t interest you. But that’s really fighting against human nature. We’re time-constrained, and social media has made it easier than ever to perpetuate our natural tendency to rely on the advice of friends for what is interesting.

So really, the best thing to do is to choose your Information Filters wisely.

What do you think? How do you select your Information Filters?

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See this post on FriendFeed: http://friendfeed.com/search?q=%22Who+Is+Your+Information+Filter%3F%22&public=1

Weekly Recap 072508: Twittering into the Mainstream

Twitter got some big play this week: 2 good, 1 bad…let’s start with good…

USA Today had a nice feature on Twitter, Twitter took off from simple to ‘tweet’ success…this quote from the article really gets it right about Twitter these days…

Twitter has become so popular, so fast, that keeping up with its fast-growing user base is a real issue. So many people now use Twitter to update friends that the system often crashes.

The outages are the markers of a company that is experiencing success beyond its expectations…

The New York Times ran a story about how companies use Twitter, blogs and other social media to keep up with customer issues and questions…

If you’re scoring at home, that’s two mainstream, huge-circulation newspapers writing positive stories about Twitter this week…if you wonder a couple years from now how Twitter became so mainstream, remember weeks like this…

But not all was well with Twitter this week…the company inexplicably chopped off subscribers from every user…there were a lot of pissed Twitterers…people threatened to leave Twitter…but when the followers were restored?…

Temporary retraction .. comes back up 50 more followers ? I can’t help it … it’s sticky”

Twitter’s je ne sais quoi

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I’ve never said jailbreaking

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SmugMug seems to have figured out FriendFeed’s visual dynamics…SmugMug pictures come thorugh big, bright and beautiful on FriendFeed, especially compared to Flickr pictures…

SmugMug pix on FriendFeed, courtesy of Dave Cohen:

Dave Cohen SmugMug Pictures

Dave Cohen SmugMug Pictures

Same pix, this time Flickr on FriendFeed:

Dave Cohen Flickr Pictures

Dave Cohen Flickr Pictures

Great advertisement for SmugMug…and the little guy is cute regardless of the photo service…

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Noticed a change in my Google Reader shares these days…I’m tending to share blog posts that I haven’t already seen a few times on FriendFeed…that means fewer TechCrunch shares…more emphasis on those nuggets that haven’t seen wide circulation yet…

Figured people were seeing the big blogs enough already…

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I got to do a guest post on Louis Gray’s blog this week…really good reactions out there in the blogosphere, which was great…blogger Barry Schwartz thought enough of the post that he wrote his own post in response, Am I Losing the Connection?

Unfortunately, Barry got the author wrong…he overlooked the “guest post” announcement at the start of the post, and naturally figured Louis wrote it…from Barry’s post…

  • Louis Gray wrote a blog post named Bloggers’ Interactions With Readers Decrease With Prominence
  • Louis Gray documents what are “interactions:”
  • “It’s these two dynamics that cause some bloggers to head onto the next stage,” explains Louis.

Sigh…I am happy the post resonated, but it’d be nice to get a little recognition…so I left a comment on Barry’s post a few days ago:

Barry – glad you liked the post. One small correction – I actually wrote that particular post. Louis was kind enough to let me guest post on his blog.

As for losing your connection to the industry. Look to people like Fred Wilson and Louis Gray as examples. I don’t think any blogger should feel the need to connect with every reader. Just like connecting anywhere else – pick your spots, right?

Despite the comment, Barry hasn’t updated his blog…Barry – you’re losing touch with your readers!…

Well, I’m not alone…Rob Diana wrote a piece on Louis’s blog, Can Microblogs Just Talk to Each Other?…Dave Winer thought it was Louis’s post…such are the benefits and perils of guest blogging…

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According to Allen Stern, Mahalo employees are busily writing articles for Google Knol…Unsure of Google Knol’s future impact on his company Mahalo, Jason Calacanis is making sure they have plenty of articles with links pointing to Mahalo pages…

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Plan to buy an iPhone this week, if they have inventory

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See this post on FriendFeed: http://friendfeed.com/search?q=%22Weekly+Recap+072508%3A+Twittering+into+the+Mainstream%22&public=1

My Cameo Appearance on Louis Gray’s Blog

I had a chance to do a cameo blog post over on Louis Gray’s blog. You can see it right now, Bloggers’ Interactions With Readers Decrease With Prominence.The gist of the post is this:

One observation to make is this: the level of interaction seems to vary by the blogger’s level of established reputation. As a blogger gets more well-known on the Web, the level of interaction declines.

This was my first-ever guest blog post. I’ve seen others do it. Pretty neat, ain’t it? Here are some things that occurred to me as a I wrote it.

Louis’s blog is a lot bigger than mine. Per Technorati, Louis is a Top 5,000 blogger. A much bigger audience than mine. He’s a regular on Techmeme. I always want to put my best content here, but I have some coverage if a post doesn’t get much traction. People who read this blog know me, and have a sense of what I’ll write n the future.  Over on Louis’s blog, there’s a much bigger audience. They’ve come to expect a certain quality. Louis’s expectations became my expectations.

The chart below is the one I used in the guest post on Louis’s blog:

Louis is a Stage 3 blogger. With that, some of the crazy experimentation I like to do (such as my stick man representation of social media interactions) is not appropriate on his blog. I was cognizant of that.

I picked a subject that is consistent with Louis’s overall blog. The role of bloggers, and their interactions is the kind of subject that Louis regularly covers. I wanted a post that fit his “brand”. So I didn’t write one of my Enterprise 2.0 pieces, because that’s not something he covers.

I took forever to write it. Weirdly, it just took me longer to finish up this post than it usually does. Probably for the two reasons listed above.

A lot of fun, and I thank Louis for letting me rent his blog for a day. Go check out my post on his blog:

http://www.louisgray.com/live/2008/07/bloggers-interactions-with-readers.html

UPDATE: My guest blog post made it onto Techmeme: http://www.techmeme.com/080722/p142#a080722p142

Smart Workers Will Figure This Out: Social Media = Career Advancement

Do you think you’ve got more to contribute to your organization than you’ve had a chance to show? I’ll bet you do too.

There have been a fair number of posts about the adoption rate of web 2.0 inside companies. In my previous work doing enterprise 2.0 product marketing for BEA Systems, I can confirm a growing interest out in the corporate world.

But interest from the higher-ups is one thing. What makes the employees actually want to wiki/blog/tag/comment/tweet?

I came across this comment on an old Nick Carr post, Web 2.0’s Numbskull Factor:

Successful adoption [of web 2.0 inside companies] is likely to be driven by the usual three support cycles involved in effective change: achieving personal benefits from using them, seeing peers achieving the same benefits and continuous management support over the 24-36 months required to embed them in business as usual.

Graham Hill, PriceWaterhouseCoopers

Graham’s three elements are spot on. In this post, I want to discuss the first two cycles he discusses. The third cycle is for another post.

Personal Benefits Come in Two Flavors

In a company setting, personal benefits mean one thing:

How will it improve my career?

I know that’s a bit crass. But I think it speaks to what energizes us to work. You want recognition that you can “bring it”.

Two ways such an outcome occurs with social media/web 2.0:

  1. Makes me better at my job and strengthens relationships with colleagues
  2. Others with the power to advance my career start to form a good impression of me

In terms of improving your work, web 2.0 apps offer a variety of benefits. That’s actually going to be future post.

The second benefit is one of reputation. I think all us who work in big companies know that reputations are vital to career advancement. You form impressions of others, which frames your view of their work. And most assuredly, others form impressions of you.

In the typical work environment, you interact with others via email, phone, team meeting. Contributions are made, but not recorded. Knowledge of your effort is silo’d and much of the good stuff we do is invisible.

Social media changes the game. As projects run through wikis, a permanent record of your contributions is created. Your comments are visible and searchable, greatly increasing their value relative to verbal contributions or email. A blog post with a good idea is accessible everywhere, at any time. It also can be shown as the spark for that killer product the company introduced. Your tagging of internal data is like Louis Gray sharing posts from Google Reader. People love your tags.

You also get to step outside of your assigned duties, and weigh in on the big issues facing the company. Always felt like you’ve got a good bead on areas the company needs to address? But your manager and peers aren’t really interested? Blog about it. Tweet about it. Comment about it. Establish your cred. If your thinking pans out, you’ve got a basis for demonstrating your contributions.

The other thing is this. Your contributions via social media need to help others. As you offer insight, decisions and ideas, others will find value in your contributions. Well beyond the normal four walls of that cubicle you’re sitting in. You can build relationships with geographies, business units and departments that are not normally in your work sphere.

To recap the benefits of social media for you:

  • Work better
  • Get beyond relying only on the annual review, create an electronic trail of your work
  • Show you can contribute to larger issues affecting the company
  • Establish relationships with people outside your daily social circle
  • Build – better yet, control – your internal reputation

Peers Getting the Benefits

This one is pretty basic. You know those mass internal emails calling out an individual or team for doing something really outstanding? Don’t you love those?

Well, social media will have some of that. You’ll be on the company portal or wiki, and you’ll see a complimentary message for someone’s work on it. If it’s anything like what I see on FriendFeed or Twitter, there will be several of these messages. A great way to give the “atta boy” or “atta girl” to someone’s work.

And everyone else seeing these complimentary messages will start to get the hint. My colleagues are starting to have an impact. I’d better participate.

Final Thoughts

Workers already have a host of channels with which to establish their reputation: project teams, emails, meetings, water cooler. For some, adding web 2.0 apps is just another thing they have to worry about.

Smart employees are going to see things differently. These tools offer the chance to better contribute, to get a better read on the pulse of the company and to better control one’s reputation. A chance to change the rules for career advancement.

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If you want an easy way to stay on top of Enterprise 2.0, I invite you to join the Enterprise 2.0 Room on FriendFeed. The room takes feeds for Enterprise 2.0-related items on Twitter, Del.icio.us and SlideShare. To see this room, click here: http://friendfeed.com/rooms/enterprise-2-0

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Smart+Workers+Will+Figure+This+Out%3A+Social+Media+%3D+Career+Advancement%22&public=1

Social Media Effect: Improve Customer Service Before It Hits Twitter

Customer service is the new marketing and you have to Engage and Respect your customers.

Joseph Rodgers, Filter 2 Evangelist, Joseph Rodgers’ Internet Marketing Blog

The above quote actually has two meanings in my mind. The first meaning is to find customers who are having problems with your product or service, and engage them out in social media. Smart companies are doing it more and more, with great examples from Louis Gray, Colin Walker and Sarah Perez.

The second meaning for me is this:

Social media puts more power in consumers’ hands than ever before, and companies need to recognize that the messages their customers post will in time become as valuable as TV commercials, online ads, and magazine and newspaper ads.

Customers should not have to make a complaint on Twitter, FriendFeed, Facebook or other social media. Rather, companies need to become more aware that the way they treat their customers is going to be broadcast, with positive or negative effects on their brands.

In my previous jobs, I know that customer service tended to be that backoffice operation.  Some guy somewhere worked on that. Not something into which many in the organization invested a lot of thought. The function is not considered strategic, and many companies figured they could outsources the work.  A 2006 article from Business 2.0 pointed out the problems with outsourced customer service.

A 2005 Gartner study predicts that 60 percent of organizations that outsource customer-facing processes will see significant numbers of frustrated customers switching to competitors.

And that was before the rise of social media. Now a customer that is dissatisfied isn’t just switching to a competitor. They’re going to tell their social networks about it.

What this means is that companies need to realize that their operational cost-center approach to customer service needs to change. A couple examples tell the tale.

Adobe Customer Service

Adobe makes some killer products. The Adobe PDF is everywhere. Photoshop continues to be quite popular. Adobe is keeping the photo processing at the leading edge. Adobe Air is the new technology for rich Internet applications. All good stuff, and clearly Adobe is maintaining its market leadership position.

Which makes it such a shame that its customer service is so weak. Here are the most recent six tweets on Summize.com for “adobe customer service“:

Now when you’re producing kick-ass products, perhaps you can get away with bad customer service. But if viable competitors gain traction and deliver comparable products, what people say about your company will make a difference. Who wants publicity like that above? And those 5 different users have 637 followers on Twitter.

Let’s look at a company that has more favorable than unfavorable publicity.

Amazon Customer Service

Amazon seems to have a particularly good (not perfect) focus on customer service. Here are the most recent six tweets from Summize.com for “amazon customer service“:

Amazon.com does this as a matter of course, and has seen the benefits. The New York Times’ Joe Nocera related his personal experience with Amazon’s customer service in January 2008. Money quote:

There is simply no question that Mr. Bezos’s obsession with his customers — and the long term — has paid off, even if he had to take some hits to the stock price along the way. Surely, it was worth it. As for me, the $500 favor the company did for me this Christmas will surely rebound in additional business down the line. Why would I ever shop anywhere else online? Then again, there may be another reason good customer service makes sense. “Jeff used to say that if you did something good for one customer, they would tell 100 customers,” Mr. Kotha said.

Final Thoughts

Customer service has not traditionally been sexy. It reflects imperfections in the product, service or in the explanations for how to use it. Who wants to deal with that?

But as companies start to see their customers talking about them in various social media, it will become apparent that all customer touch points are chanves to burnish or tarnish their brands.

Customer service groups…please step into the spotlight.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Social+Media+Effect%3A+Improve+Customer+Service+Before+It+Hits+Twitter%22

Weekly Recap 062008: Baby I’m-a Want You

Babies sure can take a long time to arrive, can’t they? I don’t want to see an update from Louis until at least an hour after their birth, even longer…first things first…

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Benjamin Golub, creator of RSSmeme, received an email from an irate blogger this week…a couple of her posts had been shared via Google Reader, and ended up on RSSmeme. She wanted them taken down…

I was surprised, as I had only seen links and partial feeds for blogs on RSSmeme…turns out, there was a full feed option…

RSSmeme does run Google ads, but Benjamin’s not getting rich off them…they offset the server costs…

Still, it did set up an issue where the full content of a blog was accessible on a different site, and the site was earning money on the content via ads…

Duncan Riley came out pretty strong in favor of the blogger…partial feeds are fine, as the reader must visit the actual blog to read the whole thing…but full feeds crossed the line…I find myself agreeing with Duncan on this one…

The cool thing about RSSmeme is that it indicates how popular an item was by the number of shares…it also tells you who did the sharing…so if someone’s interested in the full blog post based on (i) its subject; (ii) the number of Reader shares; and (iii) who did the sharing, they will click the link to read the post on the actual blog…full feeds on RSSmeme aren’t needed…

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TechCrunch posts are published under two separate users on FriendFeed, Michael Arrington and Erick Schonfeld…but the action always seems to be around Arrington’s user ID…

Looking at the past ten TechCrunch posts, Arrington’s FriendFeed has 22 Likes and Comments, Schonfeld has 2…

Why such a disparity?…Arrington is the public face of TechCrunch, so people will gravitate toward his feed even if he hasn’t written the post…Arrington follows 1,329 people on FriendFeed, Schonfeld follows 79…Arrington’s FriendFeed handle is techcrunch while Schonfeld’s is erick…so if you looking for the TechCrunch feed on FriendFeed, you’re naturally going to find Arrington first…

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Finally applied the FriendFeed Block function to a user…it wasn’t that he was hassling me, but he has a tendency to spam FriendFeed entries with unrelated things and links…he added one right after I posted a comment on one entry, which disrupted the vibe of the entry…so I finally pulled the trigger…

I actually feel bad about doing it…

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With the recent post about nudity on FriendFeed, the search term nudity is starting to show up a regular referral to my blog…not quite was I was looking for, but traffic is traffic…

Which makes me wonder what kind of search term hits Ginger Makela will get for her recent post Now That I’ve Got Your Attention with BOOBS, a Word from Our Sponsor…Ginger did ad sales for Google, so she knows a thing or two about SEO

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I did experience a few users unsubscribing from me on FriendFeed the past week or so…you write about nudity, gay marriage and Like Flickr pix with nudity, that will happen…

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Some couples on FriendFeed that I enjoy…Lindsay Donaghe and Tad DonagheThomas Hawk and Mrs Hawk

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And thanks go out to Steven Hodson for putting this humble little blog up on pedestal…if you’re not subscribing to his blog WinExtra, you should…click here to add it to your reader…

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See this item on FriendFeed: http://friendfeed.com/search?q=%22weekly+recap+062008%22&public=1

Fred Wilson’s Techmeme Challenge: Can a Little Tweet Go Big Time?

Last week, Fred Wilson asked this:

What will be the first twitter post to get picked up on Techmeme and who will post it?

It’s a good question. First hurdle is a technical issue – Techmeme doesn’t index and scan activity around Twitter.  Here’s Gabe Rivera’s response in full:

It’s hard for me to see how automated aggregation of tweets could be a net win for Techmeme. As others have said, tweets lack context, unlike blog which are much more self contained. Could tweets be reassembled into something more coherent for Techmeme? Automated processes for doing that are too error prone, at least by the standards Techmeme would demand. And even if they were perfect, the results will still look strange and disjointed. And in any case, blog posts tend to emerge quickly for the most important stories “breaking” on Twitter. Techmeme has definitely benefited from the Twitter ecosystem. For one thing, Twitter serves as a backchannel that prompts people to blog about things they otherwise would have discovered too late or not at all. Of course Techmeme publishes to Twitter too. But aggregation of the tweets themselves is a tough nut to crack.

In there, you’ll see the technology answer. He also addresses a larger issue, which is that tweets lack context as standalone content. But Fred Wilson answers that question this way:

But you can permalink to a tweet So if dozens of high profile blogs did that, then would that tweet be techmeme material and would it be right for that to be the anchor post?

Context is the name of the game here. If Gabe ever tracked individual tweets (thus solving the technical issue), I think there are two paths toward getting context.

  1. Self-evident context for the specific tweet
  2. An aggregation of comments around the tweet

These are different angles on the context subject. Let’s break ’em down, shall we?

Self-Evident Context

Fred Wilson hits the nail on the head for one way to evaluate context. What blogs are linking to the tweet?

My understanding of the inner workings of Twitter is incomplete, but one thing that’s important is whether a given party has been on Techmeme before.  Even better if said party was part of the Techmeme 100. Here’s how Robert Scoble described it:

TechMeme works partly on this principle: past behavior is best indiction of future success. So, Techcrunch gets on top for a lot of things because he’s been best in the past.

With zero tweets on Techmeme thus far, any tweet that makes it there will need an extra boost to get there. Self-evident context will be provided by two sources:

  • The Techmeme status of the person who made the tweet
  • The Techmeme status of the blogs that link to it

The Techmeme status of the person twittering is key. It’s one thing for Joe Blow to tweet “rumor: amazon.com to buy yahoo”. But if Techmeme regular Kara Swisher tweeted it, then we’re talking! There’d be the challenge of linking Boomtown Kara Swisher with Twitter Kara Swisher. But that doesn’t seem insurmountable.

The first element of context – the Twitterer’s Techmeme status – is linked to the second element, which blogs will link to the tweet. Unless we see a delphic newbie emerge, most high profile bloggers will pay attention to existing A-Listers. Here’s a visual description of all this:

This shouldn’t come across as a negative. It’s reality. The A-Listers got there by knowledge and skill, and have reputations to protect. If they put something out there, you really can put greater credence in it.

That’s self-evident context.

Aggregation of Comments Around the Tweet

The second scenario for a tweet would be the aggregation of conversations around it. The thing here is that the heat of the comments drives its placement on Techmeme. Assuming a lot of comments, and that the subject matter fits the Techmeme sphere.

But this scenario for context still requires some Techmeme juice. Both the original Twitterer and the subsequent commenters will need Techmeme status. Using the commenting from FriendFeed, here is an example:

The red boxes on the FriendFeed comments are for bloggers who regularly make Techmeme (Fred Wilson, Mathew Ingram, Louis Gray, Steve Rubel, Robert Scoble). So the presence of those comments gives the tweet the right context. It’s got Techmeme firepower.

I could see the aggregated comments for a tweet driving that tweet onto Techmeme. And FriendFeed makes it easy to track the conversations around a tweet. Which answers one of Gabe’s concerns in his comment above about tracking the contextual conversations around the tweet.

Final Thoughts

Fred ain’t so crazy. I could see a tweet hitting Techmeme, under a couple scenarios. But it will take the right combination of existing A-Lister Techmeme firepower to make it happen.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Fred+Wilson%E2%80%99s+Techmeme+Challenge%3A+Can+a+Little+Tweet+Go+Big+Time%22&public=1

Weekly Recap 060608: Ferris Bueller Was Right

The week that was…

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

Ferris Beuller, Ferris Bueller’s Day Off

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

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

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

Robert Seidman has a good post describing potential pitfalls…

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

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

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Robert Scoble, on the value of noise

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

Stop and think about that for a little while…

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

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

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

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Plurkkarma“…gonna wait on this one…

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

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

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

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

Filtering FriendFeed – How Crowdsourcing Can Solve This

It would be nice to have filters on FriendFeed. For instance, it would be nice to be able to hide any post containing the word “Obama” without having to hide someone’s other stuff. Or the ability to hide any entry containing the word “ubuntu”, etc.

Thomas Hawk, FriendFeed direct post, May 1, 2008

The need for filters on FriendFeed is a recurring topic. Click here to see the numerous entries that contain the words ‘friendfeed’ and ‘filters’. Louis Gray notes the need for this in a recent post.

I want present an idea for filters that has two pieces:

  • Category filters
  • Keyword filters

The two pieces are interrelated, and crowdsourcing will be used to build out the category filters.

Let’s get to it, shall we?

Category Filters

FriendFeed already has a “Feed Preferences” page for each member. Here is where you can manage your category and keyword filters. The graphic below is mockup of this:

A. Category Filters

Various categories will be displayed, along with a link to the full list of categories. In the example, above, I say that I’d like to filter out all FriendFeed entries that relate to politics.

The value of category filtering is that it prevents you from having to manage every keyword that might relate to a category. In a recent post, I noted Dave Winer’s 38 different politics-related terms. For instance, he used the terms: Hillary, HRC, Clinton, Edwards, Obama, Rove, etc. Having the ability to automatically filter those out without having to set up keyword hides over and over would be a great benefit to many members. Particularly as FriendFeed gains traction with a flood of new members.

Now how would FriendFeed know that Hillary, Obama, HRC, etc. are part of the politics category? Keep reading.

B. Keyword Filters

Members will need the ability to see what words they have hidden. They can un-hide keywords, or add new keywords to hide directly on the Feed Preferences UI.

Keyword-Based Hides

FriendFeed currently supports hiding specific entries, plus entries from specific members and services. For instance, you can hide all Twitter updates. What is lacking is the ability to filter out entries with specific terms in them.

For instance, shown below are three tweets from Dave Winer regarding politics:

What I’d like to do is apply the Hide function to anything with ‘Harold Ickes’ or ‘Henry Waxman’. This is a mock up of that screen below:

A. Full Text of Entry Displays

The full text of the entry appears. Each word of the entry includes a link. The links are easy ways for members to populate the ‘hide terms’ input box.

B. Hide Terms Input Box

Commas separate each term.

C. Categorize the Terms to Be Hidden

As the member hides the terms, they will be asked to apply a category. The most popular categories previously applied to the keywords will be displayed. Or the member can type a category into the input box, and FriendFeed will auto-suggest different categories with each character entered.

Why do this? This is the basis of the crowdsourced solution.

Let the People Decide

People will have a much better handle on the categories that apply to a keyword than will a heavy-duty algorithm. Such human filtering is the basis of tagging.

Two elements are relevant here:

  • The need to prevent bad categories being assigned to keywords
  • The motivation to do this categorizing

Use Bayesian Stats to Prevent Bad Categories

Here’s the issue you want to avoid. Some prankster assigns the football category to the term “Paris Hilton” while hiding all entries containing her name. Suddenly, members who are filtering out football entries stop seeing their Paris Hilton updates (yes I know, horrors…).

Enter Bayesian statistics. Carl Bialik, a columnist for the Wall Street Journal, has a great column on the use of Bayesian stats for online ratings. The gist of this approach is that all items in a rating system are born with identical ratings. Their ratings only change as people vote, and it takes a sufficient number of votes to really move the rating of an item. Here’s an example of this from the WSJ column:

For instance, as noted in the column, IMDB.com doesn’t use straight averages to list the top 250 movies of all time, as voted on by its users. Instead, each movie starts out with 1,300 votes and a ranking of 6.7, which is the site’s average. That helps smooth the effects of a few intense votes; it takes a lot of votes to budge the IMDB meter up or down from 6.7

That same approach would be applied inside FriendFeed. It would take a large number of people putting a keyword into the same category before the keyword actually became “part” of that category.

Once a keyword graduates to a category, any users filtering that category won’t see entries with those keywords.

Motivation

Why would anyone bother to categorize the keywords they hide? One answer – not everyone will. But there are two drivers of members doing some keyword categorization.

First, members need to recognize that they are contributing to a system from which they are likely benefiting. If you filter any category, you will be benefiting from the work of others’ who have categorized keywords.

Second, the categorization experience has to be simple and fast. You’ve got the member right there, motivated to hide a term. Make it easy for them to channel that motivation into a simple categorization. The most popular previous categories are displayed, making it easy check them. And the auto-suggest feature can be done fairly quickly. I like how Faviki is doing it:

Faviki draws from thousands of different Wikipedia entries for this list.

Final Thoughts

One thing to consider here is that every entry coming into FriendFeed would need to be filtered for keywords. Serious processing power will be required. Fortunately, the FriendFeed guys have firsthand experience with high volumes of real-time queries for keywords at Google.

With regard to this proposal, I haven’t (yet) seen anything on the market that will provide the category tags that would help filter FriendFeed. Since it’s the members who are most in tune with what they want to filter, their common sense and motivation should be leveraged.

As FriendFeed grows, imagine new members easily managing the flow of information by simply filtering the politics category rather than having to set up an extensive list of new keywords. It would make the experience that much better for everyone.

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See this item on FriendFeed: http://friendfeed.com/search?q=%22Filtering+FriendFeed+-+How+Crowdsourcing+Can+Solve+This%22&public=1

FriendFeed ‘Likes’ Index: Case Study in Value of Distributed Conversations

By keeping comments distributed, or decentralized, more than one discussion is able to take place. New ideas are likely to be heard since readers often start with a blank slate and are more likely to participate.

Shey Smith, introspective snapshots, The Case For Distributed Conversations

Today, a great example of the value of distributed conversations took place. What started as a blog post here ended up with three different developers coming up with innovative new scripts that FriendFeeders were digging. And it all happened because of distributed conversations, not despite them.

The very smart and in-tune Fred Wilson wrote a piece yesterday decrying the distribution of conversations all over the Web, including on FriendFeed. Mathew Ingram followed up with a concurring blog post. I understand where they’re coming from, but I think they overlook the value of distributed conversations.

What I’d like to do is briefly describe the action today, and then point out how distributed conversations made innovation possible today.

FriendFeed ‘Likes’ Index Calculators

Wednesday night, I posted a piece titled FriendFeed ‘Likes’ Compatibility Index. The post reported some number crunching I did to figure out who most often Liked the same things that I do. The idea was to see what other FriendFeeders shared the same interests. At the end of the post, I made a request for someone to automate the analysis.

From this post, two separate conversations emerged. The RSS feed for the blog post hit FriendFeed (Original Post). And Louis Gray shared it on Google Reader (Shared Post), which started a second conversation.

What happened? There were three different places where conversations were happening: on this blog and on two different items in FriendFeed. And it resulted in three separate developers coming up with solutions.

Yuvi

Yuvi, a 17-year old wunderkind who does amazing stats analysis, was interested in automating this analysis. He posted the same comment on all three locations: “I could automate this…if friendfeed fixed this bug.” Yuvi was concerned about a bug in FriendFeed that won’t allow you to go more than 11 pages back in your history.

His comment generated responses in FriendFeed on both the Original Post and on the Shared Post.

Original Post:

  • Phil Glockner: “Yuvi, does that bug exist when doing queries against the API?”
  • Yuvi: “Yes, it exists in the API too.”

Shared Post:

  • Shey: Yuvi, could you automate it up to page 11?
  • Hutch: Does the limit of going back beyond page 11 risk the script failing? Or does it limit the data collected?
  • Yuvi: @Hutch: Limits data collected.
  • Yuvi:@Shey: Well, I could… But, it’ll be of limited use, no?
  • Bwana: I say do it now so when they do fix it, it’ll be ready, plus there seems to be an interest
  • Shey: @Yuvi Limited yes, but I think 11 pages of data is of some use for analysis of recent data
  • Cyndy: Yuvi, I’m not sure it’s a bug. I think it’s a limit that they have set. Since the variable is passed in the URL, if you try to go past that number of posts manually, it still won’t go. Could be that they are only pulling from cache?
  • Yuvi: @Cyndy: Well, they’ve been mum on this – so I don’t really know. But, if even *I* can’t access my old stuff, isn’t that wrong on at least “some” level?
  • Benjamin Golub: I don’t think it’s a bug either. I feel that there DB sharding might be setup such that it is very very quick to pull recent data.
  • Bwana: Well if there is a limit imposed, pages after 11 shouldn’t even be shown. It’s a bug of some kind either way.
  • Yuvi: @Benjamin: Yep, agree on that, but there should be ‘some’ way to get the older data out, no?
  • Yuvi: Just repeating – the API has the same limit in place. Script ready anyway – First Target – LouisGray 😉

So in that sequence, you see that fragmented conversation, away from the blog post itself, resulted in Yuvi creating a script to determine who shares your Likes.

And Yuvi blogged about it, linking to my blog post and even mentioning me by name. Everything a blogger could want.

Do you see what I mean Fred and Mathew?

Ole Begemann

On Louis’s Shared Post, a second developer Ole Begemann weighed in:

  • Ole Begemann: I’ve written a Python script that does this, too (for practice). Interestingly, Phil is no. 12 on my list of Louis Gray’s most compatible likers. If there’s interest, I’ll try to wrap it up on a web page (it’s command line at the moment) and publish it.
  • Hutch: @Ole – Yeah, I’d like to have a page where you could see these results.
  • Ole Begemann: I’ll get around to it Hutch. It might take me a few days. It’s my first try as a Python programmer. 😉

A second developer came up with a script for this. Again, via conversations that happened entirely away from the originating blog.

felix

Finally, back on my Original Post in FriendFeed, a developer named felix added this comment:

“I just created a little javascript to go and grab the last 30 likes of anyone and do a basic calculation. Have a couple more features I want to add, but no more time today – what do y’all think? http://is.gd/nLc

That link goes to a blog post, where Ole links back to my original blog post. Again, as a blogger who wrote something I thought might be interesting, this is all really good stuff.

None of it occurred on my blog. And it doesn’t bother me in the least! in fact, check out felix’s blog post. You’ll see that he, Yuvi and Ole are having a conversation about FriendFeed API limits.

Why the Distribution of the Conversation Made a Difference

Three points to make here.

1. Go where the conversations are

If I’d been hung up on forcing everyone back to my blog for comments, this likely would not have been as successful as it turned out. FriendFeed offers a dead simple commenting function that makes it incredibly easy to comment. People find it easy to interact around content, rather than everyone having to travel from blog to blog to hold conversations.

Some blogger removed his RSS from FriendFeed recently, because he didn’t like all the FriendFeed comments along with it. Really? I remember the story, but can’t find the link to his blog. Seriously.

2. Connect to people outside your blog subscriber base

Digg, StumbleUpon, FriendFeed…all of these give exposure to your blog outside of those who subscribe to it or bookmark it. And when conversations about your blog occur on these venues, you’re getting vital exposure.

Make no mistake about this. A Like or a Digg or a Stumble is great. But if you really want to attract people to your blog post, comments are king. They tell people that the post is interesting, and that they better go read to get in on the discussion.

Louis Gray has a bigger, and different, community than I do. So his share of the post on Google Reader, and the subsequent conversation, attracted people who might never have bothered with my post.

felix, who developed the really cool app where you can see who shares your Likes, does not subscribe to me in FriendFeed, nor does he subscribe to my blog. I looked at his subscriptions, and we do have a number of FriendFeeders in common including Louis. I presume that’s how he found his way to the conversation about the blog post. Would he have been attracted to the blog without the conversation going on inside FriendFeed? Unlikely.

Embrace distributed conversations. They are free advertising for your blog.

3. Use the everyone search feature

Have people figured out this one yet? On FriendFeed, you can run a search for your blog post title in the ‘everyone’ tab. It can be a little hectic, but also fascinating. Click here for the everyone search for the FriendFeed ‘Likes’ Compatibility Index post.

Note that not only will you see all the different instances of my original blog post. You’ll see Yuvi’s post as well as Thomas Hawk’s post on the subject. I like seeing comments on those related posts as well.

As a blogger, I get a lot of value out of seeing who liked the blog post, and all the conversations among the different tribes. They help me improve.

Final Thoughts

Would that blog post have resulted in three separate scripts being developed if conversations only happened on the blog? No. At least not for me. If you’ve got a huge subscriber base like Fred Wilson or Mathew Ingram, it might.

But if you’re small fry, the distribution of conversations provides enormous value. Now let me go see who shares my Likes on FriendFeed…

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See this item on FriendFeed: http://friendfeed.com/search?q=%22FriendFeed+%E2%80%98Likes%E2%80%99+Index%3A+Case+Study+in+Value+of+Distributed+Conversations%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…

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See this item on FriendFeed: http://friendfeed.com/search?q=%22FriendFeed+%27Likes%27+Compatibility+Index%22&public=1

Weekly Recap 052308: If You Love Your Blog, Set It Free

The week that was…

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Things kicked off with a pair of posts about the next stage of blogging. Yes, fractured comments and all…Duncan Riley wrote Blogging 2.0: It’s All About The User. He writes: If blogging 1.0 was about enabling the conversation on each blog, blogging 2.0 is about enabling the conversation across many blogs and supporting sites and services…Louis Gray followed up with Blogging 2.0 Causing Friction With 1.0 Bloggers…Louis nicely defines the old blogging paradigm: Blogging 1.0 centered around who could: (i)Amass the most page views; (ii) Display the most ads; (iii) Get the most comments; and (iv) Attract the most RSS subscribers

As a relatively novice blogger, I pretty easily fall into the Blogging 2.0 camp…why on earth would I want to keep the conversations limited to my little blog?…that’d be a recipe for having a stale blog…

But Blogging 1.0 is still a strong instinct out there…one example: see Allen Stern’s post on CenterNetworks, Let’s Get Serious About FriendFeed; the 1995 Message Board, the Smart Consolidator and the Stolen Conversation…read not just the post, but check out some of the comments…Blogging 1.0 will die hard…

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Help! I’ve fallen, and I can’t get up!…bad week for Twitter, everyone’s favorite social chat room: outages, outages, outages…this seems to be getting progressively worse, as Twitter’s success is killing it…

To show disapproval for Twitter’s handling of these outages, several folks staged a Twit-Out on Wednesday May 21…a number of regular Twitterers went the whole day without going over to Twitter…they also hid tweets from their FriendFeed streams…even the biggest Twitterer of all, Robert Scoble, joined in…

It wasn’t met with universal love, but they made their point…oh, and Twitter did go down that day…

But one bright spot: Twitter apparently scored a new $15 million round of VC funding…

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One outcome of the twitter issues this week…some bigger names in the social media world started to embrace it much more…Jeremiah Owyang, who previously marked the date when new Twitter subscribers could not be considered as early adopters, got into it again with FriendFeed…first he posted on FriendFeed that he now had a new place (FriendFeed) to look for conversations, which elicited a bunch of hearty “welcome aboard” type of messages…

Well that got Jeremiah fired up, and went into throw-down mode: Dudes, I’ve been on FriendFeed for a while, not a late adopter…he challenged Robert Scoble to list his date of FriendFeed registration…geek cred…

Of course, if you looked at his activity stats at that time, he had no comments, no likes…but he’s much more engaged now, which is cool…he even wrote a post about FriendFeed…

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One thing I’ve noticed in some favorited Flickr photos…models wearing little to nothing…not that I’m complaining, I love art…Thomas Hawk has some strong opinions about making this even easier here

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FriendFeed now has Rooms!…Rooms are separate spaces on FriendFeed where people can direct post items, and re-share items into a Room…they accomplish two things: (i) allow a focus around specific topics to follow; (ii) remove some of the items that were considered noise by many users…

Bwana McCall (second reference in this post, nice!) has a good initial set of use cases for rooms here…my favorite is the use of Rooms for live blogging like from one of those Apple events…

One bit of hilarity was the land grab that occurred for Room topics…Michael Nielsen asked Any plans to prevent squatting? I can see people snapping up thousands of “rooms” on the off chance that one day they’ll be worth something…um, well, uh…I managed to score Web 2.0, Enterprise 2.0, Running, Obama 2008 and Coca Cola among others…no idea what I’ll do with them, but anyone’s free to join…I wonder if the Obama campaign will want their Room?

Something that Rooms will foster: an increase in FriendFeed direct posts…regular feeds from your social media sites won’t stream automatically into Rooms…

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See this item on FriendFeed: http://friendfeed.com/search?q=%22weekly+recap+052308%22&public=1