The useful convergence of data

I have only one prediction for 2008. I think we’re finally about to see the useful combination of the 4 W’s – Who, What, Where, and When.

Marc Davis has done some interesting research in this area at Yahoo!, and Bradley Horowitz articulated how he sees the future of this space unfolding in a BBC article in June ’07:

“We do a great job as a culture of “when”. Using GMT I can say this particular moment in time and we have a great consensus about what that means…We also do a very good job of “where” – with GPS we have latitude and longitude and can specify a precise location on the planet…The remaining two Ws – we are not doing a great job of.”

I’d argue that the social networks are now really honing in on “who”, and despite having few open standards for “what” data (other than UPC) there is no shortage of “what” data amongst all the “what” providers. Every product vendor has their own version of a product identifier or serial number (such as Amazon’s ASIN, for example).

We’ve seen a lot of online services solving problems in these areas either by isolating specific pieces of data or combining the data in specific ways. But nobody has yet integrated all 4 in a meaningful way.


Jeff Jarvis’ insightful post on social airlines starts to show how these concepts might form in all kinds of markets. When you’re traveling it makes a lot of sense to tap into “who” data to create compelling experiences that will benefit everyone:

  • At the simplest level, we could connect while in the air to set up shared cab rides once we land, saving passengers a fortune.
  • We can ask our fellow passengers who live in or frequently visit a destination for their recommendations for restaurants, things to do, ways to get around.
  • We can play games.
  • What if you chose to fly on one airline vs. another because you knew and liked the people better? What if the airline’s brand became its passengers?
  • Imagine if on this onboard social network, you could find people you want to meet – people in the same business going to the same conference, people of similar interests, future husbands and wives – and you can rendezvous in the lounge.
  • The airline can set up an auction marketplace for at least some of the seats: What’s it worth for you to fly to Berlin next Wednesday?

Carrying the theme to retail markets, you can imagine that you will walk into H&M and discover that one of your first-degree contacts recently bought the same shirt you were about to purchase. You buy a different one instead. Or people who usually buy the same hair conditioner as you at the Walgreen’s you’re in now are switching to a different hair conditioner this month. Though this wouldn’t help someone like me who has no hair to condition.

Similarly, you can imagine that marketing messages could actually become useful in addition to being relevant. If CostCo would tell me which of the products I often buy are on sale as I’m shopping, or which of the products I’m likely to need given what they know about how much I buy of what and when, then my loyalty there is going to shoot through the roof. They may even be able to identify that I’m likely buying milk elsewhere and give me a one-time coupon for CostCo milk.

Bradley sees it playing out on the phone, too:

“On my phone I see prices for a can of soup in my neighbourhood. It resolves not only that particular can of soup but knows who I am, where I am and where I live and helps me make an intelligent decision about whether or not it is a fair price.

It has to be transparent and it has to be easy because I am not going to invest a lot of effort or time to save 13 cents.”

It may be unrealistic to expect that this trend will explode in 2008, but I expect it to at least appear in a number of places and inspire future implementations as a result. What I’m sure we will see in 2008 is dramatic growth in the behind-the-scenes work that will make this happen, such as the development and customization of CRM-like systems.

Lots of companies have danced around these ideas for years, but I think the ideas and the technologies are finally ready to create something real, something very powerful.

Photo: SophieMuc

The Internet’s secret sauce: surfacing coincidence

What is it that makes my favorite online services so compelling? I’m talking about the whole family of services that includes Dopplr, Wesabe, Twitter, Flickr, and del.icio.us among others.

I find it interesting that people don’t generally refer to any of these as “web sites”. They are “services”.

I was fortunate enough to spend some time with Dopplr’s Matt Biddulph and Matt Jones last week while in London where they described the architecture of what they’ve built in terms of connected data keys. The job of Dopplr, Mr. Jones said, was to “surface coincidence”.

I think that term slipped out accidentally, but I love it. What does it mean to “surface coincidence”?

It starts by enabling people to manufacture the circumstances by which coincidence becomes at least meaningful if not actually useful. Or, as Jon Udell put it years ago now when comparing Internet data signals to cellular biology:

“It looks like serendipity, and in a way it is, but it’s manufactured serendipity.”

All these services allow me to manage fragments of my life without requiring burdensome tasks. They all let me take my data wherever I want. They all enhance my data by connecting it to more data. They all make my data relevant in the context of a larger community.

When my life fragments are managed by an intelligent service, then that service can make observations about my data on my behalf.

Dopplr can show me when a distant friend will be near and vice versa. Twitter can show me what my friends are doing right now. Wesabe can show me what others have learned about saving money at the places where I spend my money. Among many other things Flickr can show me how to look differently at the things I see when I take photos. And del.icio.us can show me things that my friends are reading every day.

There are many many behaviors both implicit and explicit that could be managed using this formula or what is starting to look like a successful formula, anyhow. Someone could capture, manage and enhance the things that I find funny, the things I hate, the things at home I’m trying to get rid of, the things I accomplished at work today, the political issues I support, etc.

But just collecting, managing and enhancing my life fragments isn’t enough. And I think what Matt Jones said is a really important part of how you make data come to life.

You can make information accessible and even fun. You can make the vast pool feel manageable and usable. You can make people feel connected.

And when you can create meaning in people’s lives, you create deep loyalty. That loyalty can be the foundation of larger businesses powered by advertising or subscriptions or affiliate networks or whatever.

The result of surfacing coincidence is a meaningful action. And those actions are where business value is created.

Wikipedia defines coincidence as follows:

“Coincidence is the noteworthy alignment of two or more events or circumstances without obvious causal connection.”

This is, of course, similar and related to the definition of serendipity:

“Serendipity is the effect by which one accidentally discovers something fortunate, especially while looking for something else entirely.”

You might say that this is a criteria against which any new online service should be measured. Though it’s probably so core to getting things right that every other consideration in building a new online service needs to support it.

It’s probably THE criteria.

The problem with being popular (part 2)

One of the more interesting sciences, in my mind, is how information relevance is both determined, surfaced and then evolved.

In Fred Wilson’s recent Cautionary Techmeme Tale he argues that making news popular takes away its social context and therefore becomes meaningless. He found Techmeme more useful when its sources more closely resembled his network of friends:

“For years, I’ve been using curators to filter my web experience…Techmeme has been the killer social media curator for my world of tech blogs. Lore has it that it was created using Scoble’s OPML file. It doesn’t matter to me if that’s true or not, I love that story. Because my OPML file was unusable until I found Techmeme and after that I stopped reading feeds and started reading curated feeds.”

This feeds into a larger argument about why pop culture and the art of being or becoming popular can be a bad thing. Not long ago I was inspired by the movie “Good Night and Good Luck” to dive into this idea myself:

“The real problem with popularity-driven models is that they reduce both the breadth and depth of the sources, topics and viewpoints being expressed across a community. Popularity-driven models water down the value in those hard-to-find nuggets. They normalize coverage and create new power structures that interesting things have to fight through.”

This is exactly why personalization, recommendations and social media technologies really matter. They can solve this problem of creating conformist media consumption practices by creating relevance through networks of people rather than through networks of commercial institutions.

I haven’t used My Yahoo! as much as I’d like, but there is a simple function in it that I love which could ultimately create amazing benefits for people who want a human filter for the Internet. It’s called “Top Picks”.

“The Top Picks module automatically highlights stories from your page, based on the articles you have recently read on My Yahoo! The more stories you click on, the more you will see this module reflect your interests.”

Actually, the technology beneath it is not so ‘simple’ but the application of it here makes so much sense that it feels like it’s simple when you watch it work. It works by using implicit behaviors. I don’t have to tell it what I like. It learns.

If it could also show me what my social network is tapped into right now, then the experience would feel nearly complete.

Media researchers will note here that people need pop culture to feel connected to a greater whole. I believe that’s true, too. Television is an amazingly powerful community builder.

But I would gladly trade a powerful singular social voice tied together by networks of distribution ownership for a less unified but still loosely connected network of pop culture tied together by my personal activities and my social connections.

The business of network effects

The Internet platform business has some unique challenges. It’s very tempting to adopt known models to make sense of it, like the PC business, for example, and think of the Internet platform like an operating system.

The similarities are hard to deny, and who wouldn’t want to control the operating system of the Internet?

In 2005, Jason Kottke proposed a vision for the “WebOS” where users could control their experience with tools that leveraged a combination of local storage and a local server, networked services and rich clients.

“Applications developed for this hypothetical platform have some powerful advantages. Because they run in a Web browser, these applications are cross platform, just like Web apps such as Gmail, Basecamp, and Salesforce.com. You don’t need to be on a specific machine with a specific OS…you just need a browser + local Web server to access your favorite data and apps.”

Prior to that post, Nick Carr offered a view on the role of the browser that surely resonated with the OS perspective for the Internet:

“Forget the traditional user interface. The looming battle in the information technology business is over control of the utility interface…Control over the utility interface will provide an IT vendor with the kind of power that Microsoft has long held through its control of the PC user interface.”

He also responded later to Kottke’s vision saying that the reliance on local web and storage services on a user’s PC may be unnecessary:

“Your personal desktop, residing entirely on a distant server, will be easily accessible from any device wherever you go. Personal computing will have broken free of the personal computer.”

But the client layer is merely a piece of the much larger puzzle, in my opinon.

Dare Obasanjo more recently broke down the different ideas of what “Cloud OS” might mean:

“I think it is a good idea for people to have a clear idea of what they are talking about when they throw around terms like “cloud OS” or “cloud platform” so we don’t end up with another useless term like SOA which means a different thing to each person who talks about it. Below are the three main ideas people often identify as a “Web OS”, “cloud OS” or “cloud platform” and examples of companies executing on that vision.”

He defines them as follows:

  1. WIMP Desktop Environment Implemented as a Rich Internet Application (The YouOS Strategy)
  2. Platform for Building Web-based Applications (The Amazon Strategy)
  3. Web-based Applications and APIs for Integrating with Them (The Google Strategy)

The OS metaphor has lots of powerful implications for business models, as we’ve seen on the PC. The operating system in a PC controls all the connections from the application user experience through the filesystem down through the computer hardware itself out to the interaction with peripheral services. Being the omniscient hub makes the operating system a very effective taxman for every service in the stack. And from there, the revenue streams become very easy to enable and enforce.

But the OS metaphor implies a command-and-control dynamic that doesn’t really work in a global network controlled only by protocols.

Internet software and media businesses don’t have an equivilent choke point. There’s no single processor or function or service that controls the Internet experience. There’s no one technology or one company that owns distribution.

There are lots of stacks that do have choke points on the Internet. And there are choke points that have tremendous value and leverage. Some are built purely and intentionally on top of a distribution point such as the iPod on iTunes, for example.

But no single distribution center touches all the points in any stack. The Internet business is fundamentally made of data vectors, not operational stacks.

Jeremy Zawodny shed light on this concept for me using building construction analogies.

He noted that my building contractor doesn’t exclusively buy Makita or DeWalt or Ryobi tools, though some tools make more sense in bundles. He buys the tool that is best for the job and what he needs.

My contractor doesn’t employ plumbers, roofers and electricians himself. Rather he maintains a network of favorite providers who will serve different needs on different jobs.

He provides value to me as an experienced distribution and aggregation point, but I am not exclusively tied to using him for everything I want to do with my house, either.

Similarly, the Internet market is a network of services. The trick to understanding what the business model looks like is figuring out how to open and connect services in ways that add value to the business.

In a precient viewpoint from 2002 about the Internet platform business, Tim O’Reilly explained why a company that has a large and valuable data store should open it up to the wider network:

“If they don’t ride the horse in the direction it’s going, it will run away from them. The companies that “grasp the nettle firmly” (as my English mother likes to say) will reap the benefits of greater control over their future than those who simply wait for events to overtake them.

There are a number of ways for a company to get benefits out of providing data to remote programmers:

Revenue. The brute force approach imposes costs both on the company whose data is being spidered and on the company doing the spidering. A simple API that makes the operation faster and more efficient is worth money. What’s more, it opens up whole new markets. Amazon-powered library catalogs anyone?

Branding. A company that provides data to remote programmers can request branding as a condition of the service.

Platform lock in. As Microsoft has demonstrated time and time again, a platform strategy beats an application strategy every time. Once you become part of the platform that other applications rely on, you are a key part of the computing infrastructure, and very difficult to dislodge. The companies that knowingly take their data assets and make them indispensable to developers will cement their role as a key part of the computing infrastructure.

Goodwill. Especially in the fast-moving high-tech industry, the “coolness” factor can make a huge difference both in attracting customers and in attracting the best staff.”

That doesn’t clearly translate into traditional business models necessarily, but if you look at key business breakthroughs in the past, the picture today becomes more clear.

  1. The first breakthrough business model was based around page views. The domain created an Apple-like controlled container. Exposure to eyeballs was sold by the thousands per domain. All the software and content was owned and operated by the domain owner, except the user’s browser. All you needed was to get and keep eyeballs on your domain.
  2. The second breakthrough business model emerged out of innovations in distribution. By building a powerful distribution center and direct connections with the user experience, advertising could be sold both where people began their online experiences and at the various independent domain stacks where they landed. Inventory beget spending beget redistribution beget inventory…it started to look a lot like network effects as it matured.
  3. The third breakthrough business model seems to be a riff on its predecessors and looks less and less like an operating system. The next breakthrough is network effects.

Network EffectsNetwork effects happen when the value of the entire network increases with each node added to the network. The telephone is the classic example, where every telephone becomes more valuable with each new phone in the network.

This is in contrast to TVs which don’t care or even notice if more TVs plug in.

Recommendation engines are the ultimate network effect lubricator. The more people shop at Amazon, the better their recommendation engine gets…which, in turn, helps people buy more stuff at Amazon.

Network effects are built around unique and useful nodes with transparent and highly accessible connection points. Social networks are a good example because they use a person’s profile as a node and a person’s email address as a connection point.

Network effects can be built around other things like keyword-tagged URLs (del.icio.us), shared photos (flickr), songs played (last.fm), news items about locations (outside.in).

The contribution of each data point wherever that may happen makes the aggregate pool more valuable. And as long as there are obvious and open ways for those data points to talk to each other and other systems, then network effects are enabled.

Launching successful network effect businesses is no easy task. The value a participant can extract from the network must be higher than the cost of adding a node in the network. The network’s purpose and its output must be indespensible to the node creators.

Massively distributed network effects require some unique characteristics to form. Value not only has to build with each new node, but the value of each node needs to increase as it gets leveraged in other ways in the network.

For example, my email address has become an enabler around the Internet. Every site that requires a login is going to capture my email address. And as I build a relationship with those sites, my email address becomes increasingly important to me. Not only is having an email address adding value to the entire network of email addresses, but the value of my email address increases for me with each service that is able to leverage my investment in my email address.

Then the core services built around my email address start to increase in value, too.

For example, when I turned on my iPhone and discovered that my Yahoo! Address Book was automatically cooked right in without any manual importing, I suddenly realized that my Yahoo! Address Book has been a constant in my life ever since I got my first Yahoo! email address back in the ’90’s. I haven’t kept it current, but it has followed me from job to job in a way that Outlook has never been able to do.

My Yahoo! Address Book is becoming more and more valuable to me. And my iPhone is more compelling because of my investment in my email address and my address book.

Now, if the network was an operating system, there would be taxes to pay. Apple would have to pay a tax for accessing my address book, and I would have to pay a tax to keep my address book at Yahoo!. Nobody wins in that scenario.

User data needs to be open and accessible in meaningful ways, and revenue needs to be built as a result of the effects of having open data rather than as a margin-based cost-control business.

But Dare Obasanjo insightfully exposes the flaw in reducing openness around identity to individual control alone:

“One of the bitter truths about “Web 2.0” is that your data isn’t all that interesting, our data on the other hand is very interesting…A lot of “Web 2.0″ websites provide value to their users via wisdom of the crowds appproaches such as tagging or recommendations which are simply not possible with a single user’s data set or with a small set of users.”

Clearly, one of the most successful revenue-driving opportunities in the networked economy is advertising. It makes sense that it would be since so many of the most powerful network effects are built on people’s profiles and their relationships with other people. No wonder advertisers can’t spend enough money online to reach their targets.

It will be interesting to see how some of the clever startups leveraging network effects such as Wesabe think about advertising.

Wesabe have built network effects around people’s spending behavior. As you track your finances and pull in your personal banking data, Wesabe makes loose connections between your transactions and other people who have made similar transactions. Each new person and each new transaction creates more value in the aggregate pool. You then discover other people who have advice about spending in ways that are highly relevant to you.

I’ve been a fan of Netflix for a long time now, but when Wesabe showed me that lots of Netflix customers were switching to Blockbuster, I had to investigate and before long decided to switch, too. Wesabe knew to advise me based on my purchasing behavior which is a much stronger indicator of my interests than my reading behavior.

Advertisers should be drooling at the prospects of reaching people on Wesabe. No doubt Netflix should encourage their loyal subscribers to use Wesabe, too.

The many explicit clues about my interests I leave around the Internet — my listening behavior at last.fm, my information needs I express in del.icio.us, my address book relationships, my purchasing behavior in Wesabe — are all incredibly fruitful data points that advertisers want access to.

And with managed distribution, a powerful ad platform could form around these explicit behaviors that can be loosely connected everywhere I go.

Netflix could automatically find me while I’m reading a movie review on a friend’s blog or even at The New York Times and offer me a discount to re-subscribe. I’m sure they would love to pay lots of money for an ad that was so precisely targeted.

That blogger and The New York Times would be happy share revenue back to the ad platform provider who enabled such precise targeting that resulted in higher payouts overall.

And I might actually come back to Netflix if I saw that ad. Who knows, I might even start paying more attention to ads if they started to find me rather than interrupt me.

This is why the Internet looks less and less like an operating system to me. Network effects look different to me in the way people participate in them and extract value from them, the way data and technologies connect to them, and the way markets and revenue streams build off of them.

Operating systems are about command-and-control distribution points, whereas network effects are about joining vectors to create leverage.

I know little about the mathematical nuances of chaos theory, but it offers some relevant philosophical approaches to understanding what network effects are about. Wikipedia addresses how chaos theory affects organizational development:

“Most of the focus on chaos theory is primarily rooted in the underlying patterns found in an otherwise chaotic enviornment, more specifically, concepts such as self-organization, bifurcation and self-similarity…

Self-organization, as opposed to natural or social selection, is a dynamic change within the organization where system changes are made by recalculating, re-inventing and modifying its structure in order to adapt, survive, grow and develop. Self-organization is the result of re-invention and creative adaptation due to the introduction of, or being in a constant state of, perturbed equilibrium.”

Yes, my PC is often in a state of ‘perturbed equilibrium’ but not because it wants to be.

Gatekeepers need to stop calling themselves gatekeepers

Time business columnist Justin Fox questioned the success of the new media methods in a recent post “The reign of the enthusiasts“.

He suggests the algorithms that proudly surface the deep dark corners of the Internet are actually just self-referential popularity contests. When searching for his name Justin found that the articles he’s written that are likely most influential in the real world fail to rank higher than the articles he’s written which attracted the most link love from media-obsessed blogger types, like myself.

“There are web2topians out there–Battelle and my friend Matt McAlister immediately spring to mind–who are convinced that the Googles (and Diggs and del.icio.uses and Amazons and Last.fms) of the future will do a vastly better job of steering people to what they want, such a good job that most of the gatekeepers of the current media universe will prove wholly extraneous.”

This isn’t the first time someone has accused me of being a Web 2.0 blogger. Coincidentally, the same day Justin posted this, I was mocked by a local construction worker waiting for the bus with his buddies as I passed on my way to the office. He shouted to nobody in particular,

“Man, you know what I hate? Dotcommers.” He watched me walk by stonefaced and waited for a response. The guys standing around him turned to look. Unsure still, he blurted out, “Architects, too. Hate all of them.” He got the laugh he was looking for.

Jeez, am I that boring? Or that obvious and annoying? (Please don’t say anything. I think I know the answer.)

Anyhow, Justin’s question is top-of-mind for a lot of people in the media business. Where I disagree with him and the wisdom of the media industry crowd is on the notion of “gatekeepers” or rather the need for them at all.

Perhaps the most important part of being successful in media is distribution, and the reason we’re asking what the role of the gatekeeper is today is because the Internet has disintermediated the media distribution models that helped them become gatekeepers in the first place.

Online search changed the way people access relevant information, and those who once thought of themselves as gatekeepers suddenly found themselves at the mercy of the link police, the new gatekeepers, the search engines.

Yet, Justin’s explanation of the weakness of Google’s algorithm is exactly what I think many people who get mocked for their trendy glasses, old man sport coats, carefully orchestrated facial hair events, designer shoes and man purses (I don’t have a man purse) all see improving with the introduction of explicit and implicit human data into the media distribution model. The act of hyperlinking to a web page is not a strong enough currency to hold together a market of information as big as the Internet has become in recent years. It’s a false economy.

But the link currency opened the door to the idea of using behavior to help people find things. I love Last.fm not just for the music it recommends to me but because it proves this to be true. The Internet is made of people, people with a wide range of knowledge, tastes, and interests.

Now, there will always be a role for experts, and there are many cases where being an expert is not just subjective. Experts are hugely influential on the Internet as they are in other media. But I don’t see that a gatekeeper is an expert by definition.

There will also always be a role for enablers. Good enablers are often community builders who understand the rhythms of human psychology and emotion. Henry Luce was such a man, and I think he might have been a very successful web2topian today.

If those who call themselves “gatekeepers” want to share their expertise in valuable ways, then they will need to understand how the role of human data helps with distribution of that expertise. If those who aim to be enablers of communities want to be relevant, they will find ways to do that in many of the social technologies that have proven successful in this new world.

Similarly, if the people Justin affectionately refers to as web2topians appear smug, glib or arrogant when talking about media, then they are only doing themselves and everyone in the business a disservice. Gatekeepers know better than anyone that expertise does not by definition make you important. That’s a lesson the Internet generation will learn the hard way when someday they become irrelevant, too, I’m sure.

For my wishlist: a start page that learns

I had the pleasure of joining Rex Hammock for drinks last night in Potrero Hill while he was here for Macworld Expo.

Rex is tuned in to some interesting aspects of the online world, particularly through his site SmallBusiness.com which is becoming a useful and increasingly powerful wiki. I was amazed to hear that the contributions are no longer coming from his team. The community is making the site work and building it into a resource that matters.

We also talked about RSS and start pages. Rex shares my frustration that start pages are so dependent on custom configurations that the majority of the world will never do. Machine learning and recommendations technology is not new, and it seems like such an obvious direction for the start page to go…

Show me what the world looks like through a global lens, my networks' lenses and my own personal lens. Learn from both my explicit and implicit behaviors and then adjust.

Amazon knows how to use my shopping behavior to create compelling shopping experiences. Why can’t my news reading behavior be interpreted to create a better start page experience?

The Onion understands this, too:

Amazon Recommendations Understand Area Woman Better Than Husband

Pamela Meyers said that her husband, whose gift choices have never reflected any outward recognition of her desire to learn Spanish, nor of the fact that she looks terrible in orange, rarely, if ever, communicates with Meyers while away on any of his frequent business trips.

“I was having some tea from that Nebraska Cornhuskers mug Dean got me for Valentine’s Day, when a little emai from Amazon popped up out of the blue,” Meyer said. “Just completely out of the blue.”

“It was nice to know that on my birthday, someone or something was out there thinking about me, and what boxsed sets I wanted.”

A human-powered relevance engine for Internet startup news

Here’s a fun experiment in crowdsourcing. I’ve been getting overwhelmed by all the startup news coming out of the many sources tracking the interesting ideas and new companies hunting for Internet gold. Many of these companies are really smart. Many are just, well, gold diggers.


And with so many ways to track new and interesting companies, I’ve lost the ability to identify the difference between companies that are actually attacking a problem that matters and companies that are combining buzzwords in hopes of getting funding or getting acquired or both.

There must be a way to harness the collective insight of people who are close to these companies or the ideas they embody to shed light on what’s what. Maybe there’s a way to do that using Pligg.

While shaking my head in a moment of disappointment and a little bit of jealousy at all the new dotcom millionaires/billionaires, the word “flipbait” crossed my mind. I looked to see if the domain was available, and sure enough it was. So, I grabbed the domain, installed Pligg and there it is.

It should be obvious, but the idea is to let people post news of new Internet startups and let the community decide if something is important or not. If I’m not the only one thinking about this, then I can imagine it becoming a really useful resource for gaining insight into the barage of headlines filling up my feed reader each day.

And if it doesn’t work, I’ll share whatever insight I can glean into why the concept fails. There will hopefully at least be some lessons in this experiment for publishers looking to leverage crowdsourcing in their media mix.

My personal blogger hierarchy

It’s hard to resist adding my $0.02 in a debate about blogging like the one Nick Carr started this week with his post on The Great Unread, the story of the royal hierarchy in the blogosphere:

“As the blogophere has become more rigidly hierarchical, not by design but as a natural consequence of hyperlinking patterns, filtering algorithms, aggregation engines, and subscription and syndication technologies, not to mention human nature, it has turned into a grand system of patronage operated – with the best of intentions, mind you – by a tiny, self-perpetuating elite.”

It’s definitely worth a read if you blog. If you don’t, it’s more echo chamber music, as is this post.

I suspect that the idea of the blogosphere and the blog elite is a temporary one. The blogger hierarchy does not make the substance of a post any more or less valuable. Ultimately, that value is completely up to me, not some shallow power structure.

I’m hoping that instead of reinforcing global hiearchical power structures that things like recommendation engines, personalization services, syndication and filtering algorithms will weed out the crap and bubble up what matters to me, empowering me to own my media experience.

Popular blogs, podcasts and videos will become just a sidebar to my daily intake when their relevance to my world is only tangential.

I respect what Jay Rosen says (and Nick, for that matter), but his posts are too long for me. I need the blogs I read regularly to filter out which of Jay’s posts are worth spending the time to read. I’m impressed not just by the quality of the posts Jeff Jarvis generates but also the volume. Again, I need an interestingness filter on Jeff’s posts to surface the ones that matter to me.

Yet all of Jay’s and Jeff’s influence on my thinking about journalism and media has no bearing whatsoever on the music I listen to, the basketball teams I follow or the technologies I find interesting.

What Nick rightly points out is that there will be an increasing tendency for people to publish for the sake of fame and fortune which will dilute the pool of interesting things out there. This is the popularity problem.

Perhaps I’m just optimistic. But it seems reasonable to expect that we’ll find technology answers to this issue, automatic ways to subvert wasteful power structures that may be forming in the world of personal media.

Recommending RSS feeds on My Yahoo!

Former Yahoo! colleague Don Loeb (now at Feedburner) called out the recent addition of RSS feed recommendations to the My Yahoo! product. This module automatically bubbles up sources that you might want to add to your page so that you don’t have to hunt and peck so much to find stuff that matters to you.


It’s cool to see a technology work as it was intended…but then there are the surprises that aren’t intended that are even better than seeing something go as planned.

One interesting unintended outcome is that I’m actually discovering new blog posts to read that I would never otherwise find amongst my current list of feeds. And I don’t have to subscribe to the feeds to see these posts.

For example, Niall Kennedy’s blog was recommended to me in this new module and I learned that he’d just left Microsoft after a short stay with the Live.com team. I don’t currently subscribe to Niall’s blog and none of my feeds seemed to reference this news. Very impressive.

This is another example of the “Interestingness” concept Tim O’Reilly and Bradley Horowitz have written about this week.

You can get access to the recommendations module by clicking on the small promotional link in the “Inside My Yahoo!” module that comes as a default when you sign up for an account. The reason we’re not making more noise about this pilot is because we’re in test mode to see if it works and if people like it. Plus, it feels like the kind of feature you just expect from a personalized start page anyhow.