Tag Archive for 'attention economy'

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Explaining APML: what it is & why you want it

Published on October 10, 2007 in DataPortability, with 0 Comments. Tags: , , , , , , , , , , , , , , , , , , , , , .

Lately there has been a lot of chatter about APML. As a member of the workgroup advocating this standard, I thought I might help answer some of the questions on people's minds. Primarily - "what is an APML file", and "why do I want one". I suggest you read the excellent article by Marjolein Hoekstra on attention profiling that she recently wrote, if you haven't already done so, as an introduction to attention profiling. This article will focus on explaining what the technical side of an APML file is and what can be done with it. Hopefully by understanding what APML actually is, you'll understand how it can benefit you as a user.

APML - the specification
APML stands for Attention Profile Markup Language. It's an attention economy concept, based on the XML technical standard. I am going to assume you don't know what attention means, nor what XML is, so here is a quick explanation to get you on board.

Attention
There is this concept floating around on the web about the attention economy. It means as a consumer, you consume web services - e-mail, rss readers, social networking sites - and you generate value through your attention. For example, if I am on a Myspace band page for Sneaky Sound System, I am giving attention to that band. Newscorp (the company that owns MySpace) is capturing that implicit data about me (ie, it knows I like Electro/Pop/House music). By giving my attention, Newscorp has collected information about me. Implicit data are things you give away about yourself without saying it, like how people can determine what type of person you are purely off the clothes you wear. It's like explicit data - information you give up about yourself (like your gender when you signed up to MySpace).

Attention camera

I know what you did last Summer

XML
XML is one of the core standards on the web. The web pages you access, are probably using a form of XML to provide the content to you (xHTML). If you use an RSS reader, it pulls a version of XML to deliver that content to you. I am not going to get into a discussion about XML because there are plenty of other places that can do that. However I just want to make sure you understand, that XML is a very flexible way of structuring data. Think of it like a street directory. It's useless if you have a map with no street names if you are trying to find a house. But by having a map with the street names, it suddenly becomes a lot more useful because you can make sense of the houses (the content). It's a way of describing a piece of content.

APML - the specification
So all APML is, is a way of converting your attention into a structured format. The way APML does this, is that it stores your implicit and explicit data - and scores it. Lost? Keep reading.

Continuing with my example about Sneaky Sound System. If MySpace supported APML, they would identify that I like pop music. But just because someone gives attention to something, that doesn't mean they really like it; the thing about implicit data is that companies are guessing because you haven't actually said it. So MySpace might say I like pop music but with a score of 0.2 or 20% positive - meaning they're not too confident. Now lets say directly after that, I go onto the Britney Spears music space. Okay, there's no doubting now: I definitely do like pop music. So my score against "pop" is now 0.5 (50%). And if I visited the Christina Aguilera page: forget about it - my APML rank just blew to 1.0! (Note that the scoring system is a percentage, with a range from -1.0 to +1.0 or -100% to +100%).

APML ranks things, but the concepts are not just things: it will also rank authors. In the case of Marjolein Hoekstra, who wrote that post I mention in my intro, because I read other things from her it means I have a high regard for her writing. Therefore, my APML file gives her a high score. On the other hand, I have an allergic reaction whenever I read something from Valleywag because they have cooties. So Marjolein's rank would be 1.0 but Valleywag's -1.0.

Aside from the ranking of concepts (which is the core of what APML is), there are other things in an APML file that might confuse you when reviewing the spec. "From" means 'from the place you gave your attention'. So with the Sneaky Sound System concept, it would be 'from: MySpace'. It's simply describing the name of the application that added the implicit node. Another thing you may notice in an APML file is that you can create "profiles". For example, the concepts about me in my "work" profile is not something I want to mix with my "personal" profile. This allows you to segment the ranked concepts in your APML into different groups, allowing applications access to only a particilar profile.

Another thing to take note of is 'implicit' and 'explicit' which I touched on above - implicit being things you give attention to (ie, the clothes you wear - people guess because of what you wear, you are a certain personality type); explicit being things you gave away (the words you said - when you say "I'm a moron" it's quite obvious, you are). APML categorises concepts based on whether you explicitly said it, or it was implicitly determined by an application.

Okay, big whoop - why can an APML do for me?
In my eyes, there are five main benefits of APML: filtering, accountability, privacy, shared data, and you being boss.

1) Filtering
If a company supports APML, they are using a smart standard that other companies use to profile you. By ranking concepts and authors for example, they can use your APML file in the future to filter things that might interest you. As I have such a high ranking for Marjolein, when Bloglines implements APML, they will be able to use this information to start prioritising content in my RSS reader. Meaning, of the 1000 items in my bloglines reader, all the blog postings from her will have more emphasis for me to read whilst all the ones about Valleywag will sit at the bottom (with last nights trash).

2) Accountability
If a company is collecting implicit data about me and trying to profile me, I would like to see that infomation thank you very much. It's a bit like me wearing a pink shirt at a party. You meet me at a party, and think "Pink - the dude must be gay". Now I am actually as straight as a doornail, and wearing that pink shirt is me trying to be trendy. However what you have done is that by observation, you have profiled me. Now imagine if that was a web application, where this happens all the time. By letting them access your data - your APML file - you can change that. I've actually done this with Particls before, which supports APML. It had ranked a concept as high based on things I had read, which was wrong. So what I did, was changed the score to -1.0 for one of them, because that way, Particls would never show me content on things it thought I would like.

3) Privacy
I joined the APML workgroup for this reason: it was to me a smart away to deal with the growing privacy issue on the web. It fits my requirements about being privacy compliant:

  • who can see information about you
  • when can people see information about you:
  • what information they can see about you

The way APML does that is by allowing me to create 'profiles' within my APML file; allowing me to export my APML file from a company; and by allowing me to access my APML file so I can see what profile I have.

drivers

Here is my APML, now let me in. Biatch.

4) Shared data
An APML file can, with your permission, share information between your web-services. My concepts ranking books on Amazon.com, can sit alongside my RSS feed rankings. What's powerful about that, is the unintended consequences of sharing that data. For example, if Amazon ranked what my favourite genres were about books - this could be useful information to help me filter my RSS feeds about blog topics. The data generated in Amazon's ecosystem, can benefit me and enjoy a product in another ecosystem, in a mutually beneficial way.

5) You're the boss!
By being able to generate APML for the things you give attention to, you are recognising the value your attention has - something companies already place a lot of value on. Your browsing habits can reveal useful information about your personality, and the ability to control your profile is a very powerful concept. It's like controlling the image people have of you: you don't want the wrong things being said about you. :-)

Want to know more?
Check the APML FAQ. Othersise, post a comment if you still have no idea what APML is. Myself or one of the other APML workgroup members would be more than happy to answer your queries.

Bloglines to support APML

Published on October 3, 2007 in DataPortability, with 0 Comments. Tags: , , , , , , , , , , , , , , , .

Tucked away in a post by one of the leading RSS readers in the world, Bloglines had announced that they will be investigating on how they can implement APML into their service. The thing about standards is that as fantastic as they are, if no one uses them, they are not a standard. Over the last year, dozens of companies have implemented APML support and this latest annoucement by a revitalised Bloglines team that is set to take back what Google took from them, means we are going to be seeing a lot more innovation in an area that has largely gone unanswered.

The annoucement has been covered by Read/WriteWeb, APML founders Faraday Media,?Ç? and a thoughtful analysis has been done by Ross Dawson. Ben Melcalfe had also written a thought-provoking analysis, of the merits of APML.

What this means?

APML is about taking control of data that companies collect about you. For example, if you are reading lots of articles about dogs, RSS readers can make a good guess you like dogs - and will tick the "likes dogs" box on the profile they build of you which they use to determine advertising.?Ç? Your attention data is anything you give attention to - when you click on a link within facebook, that's attention data that reveals things about you implicitly.

The big thing about APML is that is solves a massive problem when it comes to privacy. If you look at my definition of what constitutes privacy, the abillity to control what data is collected with APML, completely fits the bill. I was so impressed when I first heard about it, because its a problem I have been thinking about for years, that I immediately joined the APML workgroup.

Privacy is the inflation of the attention economy, and companies like Google are painfully learning about the natural tension between privacy and targetted advertising. (Targetted advertising being the thing that Google is counting on to fund its revenue.) The web has seen a lot of technological innovation, which has disrupted a lot of our culture and society. It's time that the companies that are disrupting the world's economies, started innovating to answer the concerns of the humans that are using their services. Understanding how to deal with privacy is a key competitive advantage for any company in the Internet sector. It's good to see some finally realising that.

Understand your content

Published on September 24, 2007 in Attention economy, with 0 Comments. Tags: , , , , , .

I picked up a book my parents used on their recent trip to Greece, which was a guidebook of the Peloponnese. Flicking through this paper book reminded me of my thoughts of how the content business is so rife with piracy. Especially with an online world now, people can copy content - images, text, audio - and mash it up into their own creation. It seems crazy but why do people enter a business like that?

The Information Sector is not only a big money maker, but very unique as well. Yes, it can be copied and ripped off - unlike a barbie doll where its form can't really be manipulated into a new product. However different from selling barbies, is that information products do things that are very unique in this world and extremely powerful. In my view there are four types of information product, which can be explained under the categories of data or culture.

Data

New data
A friend and aspiring politician, once said to me that "information is the currency of politics". Reuters, the famed news organisation that supplies breaking news to media outfits across the world - derives 90% of its revenue from selling up-to-the-minute financial information to stockbrokers and the like who profit on getting information before others. New information, like what the weather will be tomorrow, loses value with time (no many care what the weather was eight days ago). But people are willing to pay a price, and a big one, to get access to this breaking news because it can help make decisions.

Old data
On the flip side, old information can be very valuable because of the ability to conduct research and analysis. Search engines effectively fit into this segment of the information economy, because they can query past news and knowledge to produce answers. Extending the weather example, being about to find out that data eight days ago along with the weather exactly one, five and ten years ago - can help you identify trends that, for example, validates the global warming theory.

Culture

Analysis
The third category of information products, I call them simply analysis because what they are is unique insight into things. We all have access to the same news for example, but it takes a smart thinker to create a prediction, by pulling the pieces together and creating new value from them. Analytical content usually gets plagiarised by students writing essays, but its also the stuff that shapes peoples perceptions in world-changing ways.

Entertainment
One of the most powerful uses of content is the way it can impact people - entertainment type content is the stuff that generates emotion in people. Emotions are a key human trait that you should keep in mind in any decision - no matter how logical someone is, the emotional self can overtake. A documentary that portrays an issue negatively, and that can generate an angry response in a person, is the stuff that can topple governments and corporations.

Not all information is equal
If you are a content creator, you need to accept that other people can copy your creation. The key is to understand what type of content you are creating, and develop a content strategy that exploits its unique characteristics.

Information products need different strategies in order to effectively monetise them. Below is a brief discussion which extends on the above to help you understand.
New data
With this type of content, the value is in the time; the quicker that information can be accessed, the more useful it is. News items (like current affairs) fit into this category. As a news consumer, I don't care how I get my news, but I care about how quickly I can get it. It's for this reason I no longer read newspapers, yet through various technologies like RSS and my mobile phone, that I probably consume more news than ever before.

You should sell this data based on access - the more you pay, the quicker the access. Likewise, the ability to enable multiple outputs is key - you need to be able to deliver your content to as many different places as possible: SMS, email, RSS etc. You should not discriminate on the output; the value is on the time.

If you create news breaks, why are you wasting your time on who can access that information, because of the threat that someone can copy it? If the value is in the time, who cares who copies it because by the time they republish it, its already lost value. A flash driven site like the Australian Financial Review is an example of a management that doesn't realise this.

Old data
A recent example of action in this space is the New York Times who have recently removed their paid subscription wall, which was previously only available via subscription but now can be accessed by anyone for free. This is a smart business move, because if you are selling archived content, you will make more money by having more people know what exists. A paid wall limits people using it which decreases the opportunity for consumption: you a relying on a brand only to create demand. If you are website with a lot of historical content - restricting access is stupid because you are effectively asking people to pay for access to something that they have no idea what value it holds for them. It's a bit like traveling - if you've never been overseas, you don't know what you are missing out on. Give people a taste of the travel bug, and they will never be able to sit still.

Unlike new data where the value is based on time, old data finds value on accessibility. People will place value on things like search, and the ability to find relevant content through the mountains of content available. Here the multitude of outputs doesn't matter, because researchers have all the time in the world. What matters is a good interface, and powerful tools to mine the data: the value is on being to find information. You shouldn't charge people on access to the content; where you will make money is on the tools to mine the data.

Analysis
This type of content is difficult to create, but easily ripped off by other people - just think of how rife plagiarism is with schools and universities, where the latter treats plagiarism as a crime just short of murder. You can distinguish this type of content as it demonstrates the ability to offer content that is was produced from a common set on inputs that anyone could access, and creating a viewpoint that only a certain type of person could create. The value is on the unique insight.

Despite the higher intlellect to product, it unfortunately is content that is harder to capitalise on. A lot of technology blogs feel the pressure of moving into a more news style than analytical service because news is what gets eyeballs. If you are a blogger looking to make money - the new data approach above should be your strategy. But if you are a blogger trying to build your brand - do analysis. The consequence with analysis is that its harder to do, so you shouldn't feel pressured to produce more content. I've noticed a trend for example, that if I post more blog postings, I will get more traffic. But on the same token, more postings puts more pressure on me, which means less quality content. Understand that the value of analysis isn't dependent on time. Or better said, the value of analysis is not how quickly it gets pumped out and realised, but how thoroughly it gets incubated as an idea and later communicated.

The value for analysis is clarity and ability to offer new thoughts. To look at the relationship with advertising models, new data like news (discussed above) typically gets higher viewers - which works for the pageview model (the more people refreshing, the more CPMs). Analysis, on the other hand, works with the time spent model. Take advantage of the engagement you have with those types of readers, because you are cultivating a community of smart people - there can be a lot more loyalty with that type of readership.

Entertainment
My sister downloads the Chaser's War on Everything as a podcast. She first came across them on the radio, but she now downloads the podcasts religiously. Even though I knew about the Chaser's efforts for years in their various products, I didn't realise they were still around. If the last few weeks, I have been noticing my friends bring up the shows they are doing. The value in this content was the ability to make people laugh, due to their unique stunts. Their brand is built because of word of mouth recommendations.

Like analysis, entertainment can be a very hard thing to generate because it relies on unique thinking. With a strong brand, people will pay for access to that content. Although it may seem that the viral spreading of funny content for free is a nightmare for a content producer trying to collect royalties, it's actually a good thing because it entrenches the brand: more people will find out about it. The nature of entertainment, like analysis, is that it is difficult to do repeatedly. Sure people can copy your individual tricks - but they can only do so after the fact. They can't pre-anticipate the next thing you will do; because unlike breaking news which is on how quickly you can pump out content, entertainment content requires a unique creative process to produce it.

The key with entertainment content, is to build a relationship with an audience and to sustain it. Create a predictable flow of content. Encourage people copying it, because all it does it get more people wanting to see what you come up with next. If it wasn't for Stephen Colbert's clips on Youtube, I would never have realised his brilliance. Not knowing he existed, means a DVD set of his shows means nothing to me (but which holds a lot of value now). The value of entertainment is to generate emotions in people repeatedly. Emotions are a powerful influence on human behaviour - master that and you can be dangerous!

Concluding thoughts
This posting only touches on the issues, but what I suggest is that creators of content need to look at what type of content they are producing, for them to exploit its unique aspects. Content represents human ideas, and content isn't distiguished by a physical form. The theft of your content should be a given and can actually help you. Depending on what that content is, there may be natural safeguards that make it irrelevant (ie, the time value of news).