How to compute someone’s Whuffie

Imagine yourself in a world where nanotechnology has made scarcity and the associated traditional form of money a thing of the past. In this world, the only currency is the goodwill that people give electronically to one another and everyone’s overall resulting reputation score is accessible by anyone in real-time. This reputation is Whuffie and the term and world was coined and imagined by Cory Doctorow in his sci-fi novel, Down and Out in the Magic Kingdom.

Fast rewind to present time. We are a world where people increasingly publish digitally their life i.e. are “life streaming”: they publish pictures, blog posts, twits, videos, wikis, etc. Other people subscribe to these life streams (RSS/friendfeed), give attention to the ones they find the most relevant and sometimes comment positively or negatively on these life stream items. These comments are themselves life streaming items and subject to views and positive/negative comments from others.

One thing is missing to get us closer to Cory’s vision: real-time computation of anyone’s Whuffie, the Web 2.0 equivalent of your FICO score. How do we compute it?

I have only found one blog post so far on the the problem of the so-called Whuffie algorithm, but I was not convinced by the arbitrary number of points won/lost for specific actions, and by the difficulty of implementing the tracking of some of these actions:

Trash talk somebody: -1000
For every conference you attend: +200 (Plus bonus +5 for each #tweet)

I know that Jeff Ward wrote that he was just posting for fun on this one, but since there seemed to be interest in the comments for an actual implementation, I decided tonight in BART to take a stab at what such algorithm would look like.

Here are the basic principles:

  • The algorithm should take into account how many positive/negative comments or citations your life stream items have got from other people, weighted by the Whuffie score of each of these people.
    • The use of the weight here is important as it allows to remove completely the arbitrary point amounts: for instance, instead of “For every conference you speak at: +10,000″, speaking at a conference would essentially be equivalent to posting a summary of your speaking engagement and have the conference organizers or the conference itself comment on it/cite you on their Web site, with the Whuffie value of the comment being a function of the Whuffie of the conference or conference organizers themselves.
    • The positive/negative nature of the comment would be determined via semantic analysis or microformats votelinks or voting nanoformats (vote:for:this article, +1/-1).
  • If the positive/negative nature of the comments cannot be determined, a positive Whuffie point amount of a lesser amount would be attributed, weighted by the Whuffie of the entity issuing the comment.
  • If no comment is available, views should be used (# of time a video was viewed), agained weighted by the Whuffie of who viewed it if possible. Views should contribute less Whuffie points then comments.
  • In all cases, for each item published a number of points should be provided multiplied by the number of followers the person/entity has on the site where the life stream item is posted on (# of subscribers to RSS feed, # of Twitter followers, # of Flickr contacts, etc.).

I don’t really have a precise idea of what these point amounts should be. Let’s say +10 for a positive comment, -10 for a negative comment, +5 for a comment, +3 for a view, and +1 for a published item.

Let’s also say that these points would be weighted by 1/100 of the Whuffie of the person commenting, viewing or following the publisher/life stream item. so, if my Whuffie is 1,000,000 and I view an image of someone, but do not comment on it, that gives 10,000 Whuffie points to the person who posted this image.

Of course this algorithm reduces the number of arbitrary constants to a few, but these are still arbitrary. So, the next question that came to my mind is whether there is a set of constant values that would be better than another, better for instance at achieving the goal of a Whuffie system.

What is such goal? do we want a bell curve distribution of Whuffie scores, a very spiky curve or a very flat curve. Do we want Whuffie to last indefinitely, or to self-destroy over time (with the objective of preventing social capital to be too concentrated among too few people). I think this is where I should have started, but that I will the subject of another post hopefully. In the meantime, I will get good ideas/suggestions from you.

Another interesting problem is how we fight spam and reputation hacking in such a system. I think one partial answer would be to allow Internet hosts to have their own Whuffie, and to use that as an additional weighting factor. Ideas here are welcome as well.

The problem with banking innovation and how to fix it.

Allen Weinberg has a great report on the first day at Payments 2008 that confirms some of the thoughts I’ve had in the past few weeks: that non-banks are becoming the primary source of banking innovation, threatening to relegate banks to mere accountants.

Allen cites the difficulty for banks to hire innovative employees because their lack of coolness, and I partly agree, but I think that is a bit too imprecise. It’s a bit like saying “We failed b/c we are were not lucky”. I think smart innovative employees go to companies that have an innovative management environment and culture, and there are very practical ways to create such an environment and culture, if the top management wants to.

To me such a culture starts by embracing the facts that:

  • Committee planning does not work for innovation because most innovations fail and slight differences between similar projects can be huge key factors of success, and as a result it is impossible to predict from which team innovation will come from.
  • People with innovative ideas (ex. new online service, new investment theory) as well as execution capabilities (ex. coding, sales skills) are a company’s greatest human asset and should be given opportunities before they leave and join a company that does.

Such an innovation culture consists then in implementing a management policy where such people can submit their plans, get a green light to allocate part of their time (whatever their direct manager says) and get a bootstrap budget as necessary. Then, just like a good option portfolio manager, define progress/success metrics, and allocate more resources to those with the most traction. And finally, reward success. All of this is something Google seems to be doing very well.

Banks are now at a most critical time and their ability to innovate in sustainable business models will be key to their survival. Nouriel Roubini noted this morning that banks’ unsustainable “originate & distribute” business model of the last few years is crumbling with the broken “securitization food chain”.

Banks are social intermediaries, and as a result, social services that focus on social lending or social saving pose a major threat to them, but could also turn out to be a major opportunity if they manage to re-intermediate these relationships and combine it with their unique competitive advantage: creating money from thin air.

Think for instance about the idea of a “college car” savings account solely dedicated to buying a car and that grand-parents could contribute too knowing where the money would end. Think of the negotiating power the bank could have by aggregating all the buying power behind these savings account and exchanging secured rebate from car manufacturers with secured future sales. This is what SmartyPig does, but environment/culture aside, it seems to me much easier to do it from the inside of a bank than from the outside. John Gaskell, SmartyPig co-founder was quick to comment that they have a patent pending on this process, so banks may actually not have this option.

Think also how a bank could leverage the fact that 50% of your student loan on a peer-to-peer lending site comes from your mum and dad, and grand-parents, and how little risk it would be for a bank to lend the remaining 50%, especially if the bank gets preferred re-payment rights.

Banks have some of this social data, in a way that is most likely much more authentic than a Facebook (think about all the documents you need to provide to open a checking or brokerage account compare to what you need to provide to open a Facebook account). It is just a matter for them to put in place the right environment and culture in place to attract people.

If they cannot change their culture, their next best bet might be to do what Apple or Facebook do: expose some of this information via easy-to-use APIs in a way that is more secure than their startup competitors. Then, allocate a VC fund to fund startups using this API (which is equivalent to buy an option to invest more/buy out the most promising ventures later).

What business model for decentralized social networks? decrypting Matt Mullenweg’s recent keynote

Decentralized social networks seem to be the talk of the town these days (in tech circles at least). Blogger Robert Scoble has given attention and created a minor scandal of a Facebook policy that forbids the use of scripts to extract data from Facebook Web pages (Note: Facebook just recently allowed accounts to be closed). Around the same time project DiSo has started with the goal to build a decentralized version of Facebook based on the open source WordPress personal publishing platform, and workgroup DataPortability.org has kicked off to define best practices to make personal data easily movable, reusable, remixable, etc. across Web services. Just two days ago at his Northern Voice 2008 keynote, Matt Mullenweg, creator of WordPress, seemed to be almost hinting at what his company was up to with their recent $29.5M round of funding: a better, open-source alternative to closed social systems like Facebook that would use social filters to bring more relevant content.

Matt Mullenweb at Northern Voice 2008

As I mentioned in my previous post on business platforms of Web companies, one key aspect of these business platforms is that “they retain control over who gets to see the information and how”. Having a point of mediation is an essential part of online capitalism. Without it, there is no point of value extraction and no big business.

The natural question then is: if so many techies are excited about the inevitable advent of decentralized and portable social networks and related personal data, and if that means essentially that there is little point of control anymore for these Websites, how are businesses going to make big money out of this?

If we put aside the ad-based revenue model that Matt M. does not seem to keen on, as well as the “pro account” business model that would expand on some existing commercially available pro services, as well as the usual ways of making money with open source, here are two models that I think could work:

  • Relevancy services: This is would be an expansion of services such as Akismet, WordPress’ spam filtering service, which is currently free for personal use. Matt insisted strongly in his keynote how content relevancy (i.e. no spam) is really what users value, and how spam from bad users is what kills social systems. Perhaps a high-quality filtering system that would combine the Akismet filter and a social filter (a filter based on your social graph) is something people would be ready to pay for.
  • The ring tone business model. This model consists in deriving transaction fees from digital goods sold on WordPress.com, such as themes and widgets. Because WordPress.com knows which blogs use which themes and widgets, this would be easily done there. It may be a bit harder for users of the WordPress open source software itself. This would be the equivalent of the ringtone business. Matt Mullenweg revealed himself that “People want their online presence to be an expression of themselves and in that regards, being able to customize the design is critical”. Matt even compared a blog as a locker, which are typically heavily personalized.

This list does not mean to be exhaustive, but seeks only to start a discussion on a subject that is getting more and more relevant. I would be curious to see what others think.

Social Network visualization in string art

String art is the art of arranging strings to form geometrical patterns. One fun way to do string art is with a piece of wood, nails and thread. Schauleh had a lot of yellow spare thread so we decided to spent last Sunday’s rainy afternoon doing some string art.

On our way to the hardware store, we were discussing what could be the inspiration for our little art project and we quickly agreed that it would be fun to do our Facebook network in string art, or at least part of it.

The result is below. Mine represents my closest friends in San Francisco and my immediate family in France, hers represents her family in Northern California. Each nail represents a person and each string represents a connection between two persons. The length of the string is proportional to the geographical distance between the two connected persons.

Guillaume's social network in string art
Schauleh's social network in string art