Complexity

An article by Gazimoff    No Comments

There’s been a fair amount of discussion recently on some research being undertaken by the Augmented Social Cognition team at the Palo Alto Research Centre. They have a simple mission: “understanding how groups remember, think and reason”. With this in mind, they recently started data-mining Wikipedia’s vast archive of user interactions in order to spot trends and understand what it says about Wikipedia. The statistics that have been heavily cited were that the growth rate of Wikipedia had slowed dramatically, both in the total number of edits and the total number of active editors. A follow up study indicated that the only group to have increased output was those with 1000 or more edits, while users with very low edit counts were up to 25 times more likely to have their changes removed or “reverted” than more seasoned users.

Even more interesting are the responses from Ed H Chi on the results he provided to New Scientist and The Guardian. Chi describes that there is “evidence of growing resistance from the Wikipedia community to new content” and that “Over time the quality may degrade”. He adds “To power users it feels like Wikipedia operates in the way it always has – but for the newcomers or the occasional users, they feel like the resistance in the community has definitely changed”. Startling stuff indeed.

Even more curious is how the growth model has changed over time. Chi starts off with stating that Wikipedia followed the hockey-stick growth that other popular sites such as Twitter and Facebook also experienced. However, over the last few years, the data no longer fit the model. In fact, follwoing their initial survey, he likened it to a population growth curve, where there’s a resource constraint that the population encounters. “As you run out of food, people start competing for that food, and that results in a slowdown in population growth and means that the stronger, more well-adapted part of the population starts to have more power.”

So, what is the limiting resource that has dramatically changed the editing demographic? Well, for a year I heavily edited Wikipedia, starting there in Feb 2008 and becoming an admin in August last year. About a year later in March 2009 I stopped editing and retired. It wasn’t that Wikipedia no longer held an interest for me – far from it. It was just that I felt I no longer had anything to offer the site as it was apart from performing the routine administrative tasks of blocking vandals and removing content. In that time though, I learned a huge variety of policies, content guidelines and regulations about what could and could not be placed on Wikipedia. It’s this area that I think is the finite resource that Ed Chi talks about.

Let’s be honest, Wikipedia contains mistakes. Some of those mistakes are trivial, but some have caused real harm to companies, institutions or living people. As a result, policies sprang up about how content should be sourced and referenced, so that it can be verified to be true. Anything that doesn’t conform to these policies gets removed sooner or later, including additions that might be accurate but that remain unsourced. More than this though, Wikipedia editors will argue passionately and at length on a huge range of topics from date formatting to fringe science topics, and as such a range of peripheral-content policies such as a manual of style together with further processes for removing content have sprung up. There are even processes specifically designed for dispute resolution, as well as the management and eventual block of users who don’t adhere to the many rules now in existence. This is the limiting factor, the finite resource that Chi refers to in his research.

The inability of the average new population member (Wikipedia editor) to be able to quickly and easily understand all of these rules before they start editing is a real handicap to the further growth of the project. It’s what the growth curve has changed – as further complexity has been added to the project, the ability for a new user to be able to participate effectively is reduced. It’s why sites like Facebook and Twitter still enjoy phenomenal growth – they rely heavily on making the experience as easy and straightforward as possible for their users, and anything that adds complexity to the experience is removed. Conversely, Wikipedia requires users to become familiar with it’s complexity before they even start contributing

So, how does Wikipedia return to the meteoric growth it once enjoyed? As with so many other services, simplification is the key here. While some veteran users are comfortable with how the rules set has evolved, it has reached the stage where the barrier to new participants is too high to be able to recruit at a sustaining rate. Without being able to convert more new users into longtime editors through a simplification of the rules set, growth is likely to tail off and eventually decay. Whether this can be achieved by Wikipedia, or by someone else bringing in a new model and user experience remains to be seen.