Collaborative Recommendation 3.0

Every now and then someone asks 'Why don't you build Collaborative Recommendation into Particls'.

In case you don't know, Collaborative Recommendation is when a system uses the recommendation of many people to 'decide' that a piece of content is worth seeing. So, like Digg for example, if 100 people vote that something is great (vote is a word I use loosely here), then it is probably worth seeing.

There are a few answers to that question.

1. Particls is really about filtering noise out - not discovering new recommended content (even though we provide some of that functionality just to get novice users started).
   
2. There are plenty of other great collaborative recommendation services out there, stick the RSS feed into Particls and there you go.
   
3. Google's PageRank and Technorati's Authority is already a form of Collaborative Recommendation - it isn't really very new.
   
4. The next generation of Collaborative Recommendation is actually something different. Let's call it Collaborative Filtering 3.0 or... Peer LifeStreams + Personal Relevancy

You have friends (hopefully); they have lifestreams (or at the very least RSS feeds from all their social/sharing sites) - plug their feeds into Particls and we filter out the stuff you don't care about. What's left? Stuff your friends 'recommended' that you actually care about. Collaborative Recommendation done right.

If you want to add me to your Collaborative Recommendation lineup, you can find me on Jaiku

Digg stuff from inside Touchstone

Right click on items on the Ticker or any Touchstone Alert and you can now Digg/Reddit/Del.icio.us/Etc it right there!

Developers can even add their own 'ActionExtensions' by writing a little bit of XML.

Have fun!

Announcing second intake of participants for the APML Workgroup

Today we are announcing a second intake of participants in the APML Workgroup. APML stands for Attention Profiling Markup Language.

From the website:

APML will allow users to export and use their own personal Attention Profile in much the same way that OPML allows them to export their reading lists from Feed Readers. The idea is to boil down all forms of Attention Data - including Browser History, OPML, Attention.XML, Email etc - to a portable file format containing a description of ranked user interests.

The new participants are:

• Sam Sethi (Vecosys)
• Daniel Winterstein (ThinkTank Maths)
• Steve Williams (Programmer, Digg)
• David Cancel (Co-Founder, Compete.com)
• Richard Giles/Graeme Sutherland (Co-Founders, Scouta.com)
• Elias Bizannes

They join the existing group:

• Chris Saad/Ashley Angell (Co-Founders, Faraday Media/Touchstone)
• Paul Jones (Senior Architect, Faraday Media/Touchstone)
• Mitch Ratcliffe (Co-Founder, Buzzlogic)
• Chris Messina (Citizen Agency)
• Daniela Barbosa (Solutions Architect, Dow Jones)
• Phil Morle (VP Attention, Yoick)
• Ben Metcalfe (Social Media Consultant)

The APML Workgroup is tasked with converting the current specification into an agreed standard.

It has already started its work with a revised spec. More information can be found on the APML website at www.apml.org

We invite all the players in or around the Attention Economy to join us in refining, implementing and evangelizing APML. To join the Workgroup please contact us with your qualifications.
Members of the general public are invited to join the mailing list (via the APML.org website) forums or blog to provide feedback.

More about APML
In a world where our online footprints (Attention Data) are measured, dissected, analyzed and used to better target us with content and advertising, APML represents a way for users to take back control of their own Attention Profile.

In order for the study of 'Attention' to evolve into the Attention Economy we must have a way to export, own, trade and assign value to our own Attention Profiles. APML promises to become an important part of the solution and we believe this announcement is a significant milestone in it's development.

Attention Profiles will become our digital fingerprints and will eventually have implications for all aspects of our lives including Media, Business and Lifestyle.

Stay tuned...

Touchstone in your referrer stats - Audiences of One

People have started to notice Touchstone in their referrer logs. So I thought I would write a little about it.

I don't think anyone will ever see a 'Digg Effect' style mad rush from Touchstone. So we probably wont make headlines that way.

So what does a referrer from Touchstone mean?

I think it means something significant. Maybe even more significant than the Digg effect. It means that your article got through the Touchstone Personal Relevancy filter of our Attention Management Platform and connected with at least one person.

One person might not sound like much, but consider that one person after another might turn into hundreds and thousands. Consider also that each of those people are intimately interested in what they came to see.

Not only that - but the user clicked through (despite seeing your headline and synopsis) from inside the Touchstone UI.

With this in mind, Touchstone traffic could become a great measure of your sites ability to intimately connect with audiences of one - people just like you. People that might want to buy what you are selling.

Digg to Support OpenID, Mine Attention Data and looking at APML

Lots of chatter today coming out of Future of Web Apps conference about Digg founder Kevin Rose's talk.

Kevin discussed supporting OpenID and mining Attention Data in an effort to create more personal news for users.

There has been quite a bit of discussion about Digg's implementation of APML as well.

These are all good moves by Digg to open up it's platform and play nice with others.

The Wizards of Buzz - The influencers deciding what's cool on our behalf

The Wall Street Journal has an interest post about "The Wizards of Buzz".

From the article:

"Most sites are based on a voting model. Members look around the Web for interesting items, such as video clips, blog entries or news articles. A member then writes a catchy description and posts it, along with a link to the material, on the site, in hopes that other members find it just as interesting and show their approval with an electronic thumbs-up vote. Items that receive enough votes rise in the rankings and appear on the front page, which can be seen by hundreds of thousands of people. When an item is submitted by a popular or influential member -- one whose postings are closely followed by fellow members -- it can have a much better shot at making the front page."

It's a little scary. They imply that services like Digg, Reddit and Netscape have made influencers out of little-known everyday people. Why is that scary? Because we don't know these people. They have not been vetted by public opinion and to many users they are an opaque part of the process. It's not democracy if there is a small group of people pulling the strings.

No one diggs around digg looking for the 'Top Diggers List' - in fact now they CAN'T dig around Digg for it - because Digg has taken it offline. Check out the article to get a list of the top Digg, Reddit, Netscape and StumbleUpn user they found. It's not a list of people I want deciding my news for me.

So these popularity platforms are giving rise to micro-influencers who are actually having a huge affect on our news and information choices and most of us have very little idea who they are. That doesn't sound very social, transparent or desirable to me.

As I have said in previous posts - while popularity engines are fine for working out "what's cool" the real question should be "what is personally relevant: - finding news that affects my life and aligns with my interests.

Then, the only influencer in my media consumption is me and my Attention Profile.

Jason Calacanis thinks having top influencers is great. I guess he would because he also thinks paying the top contributors is great too. I'd invite him consider the Personal Relevance angle (he seems to be taking up challenges this month so why not).

Thanks to Marianne for pointing out the WSJ post to me.

Creating passionate crowds

I've posted before about Digg and its deep underlying philosophical difference to Google. To recap, while Digg uses explicit 'Wisdom of crowds' approaches to generating a front page, Google uses an algorithm (which takes into account implicit votes based on links) to generate its Google News front page.

These are fundamental and philosophical differences and when the issue of Digg gaming came up (and will come up again I'm sure) it was an important discussion to have.

In fact, I recently came across a wonderful article from Kathy Sierra called 'Dumbness of Crowds' where she rightly states that the term 'Wisdom of Crowds' was actually meant in sarcasm. It was supposed to highlight that crowds (read: mobs) are actually quite stupid. Real intelligence comes when measuring individual actions in aggregate (and even then in some applications and not others - e.g. designing by committee produces bland or Frankenstein results) - rather than giving individuals collective and visible control over a process.



As I've stated before, the problem with both Digg and Google is that in an era of hyperchoice and information overload these engines only show 'What's popular' instead of 'What's Personally Relevant',

Today, however, DayLife launched, to a little criticism from one of its investors (who just happens to be Michael Arrington). It has been a long time coming and, as a result, seems to have felt a little 'over anticipation' from some in the community.

Worse still (shock/horror/sarcasm) it does not use the "Wisdom of Crowds" OR a Popularity Algorithm to generate its front page. It in fact proudly and loudly declares that it uses a 3rd, age old technique - human editors.

I'm sure the DayLife founders are very passionate about their company and I wish them best of luck with their plans. Maybe in a noisy media landscape, A site that shows simple, visual and effective headlines on the front page will be a refreshing change?

Personally though I look forward to the 4th 'front page' philosophy/technique. Using a Personal Relevancy engine to generate a front page.