Social Networking websites & a theory of cumulative advantage

(or the rich get richer effect)

Duncan Watts (author of Six Degrees) wrote an article in the New York Times about the rich get richer effect. He reports on a series of experiments on the web where they tracked the rise in popularity of music in different "parallel worlds" where participants could either see what others were doing (social influence condition) or not (individual conditon). Their main findings were that in the social influence condition (where participants could see what others were doing), the hits were much more popular (and unpopular songs more unpopular) than in the individual condition (where participants could not see what others were doing).

Also, within the social influence condition, the 8 different parallel worlds (users could only see what others were doing within their own world) displayed very different popularity patterns (different groups of songs were popular). Watts explains this unpredictability with the "rich get richer effect". Simply put - people like what others like (specifically – what those in their clique like). The first few users of a system end up playing a huge role in setting trends - people who follow are influenced by them. As such the same set of songs had very different winners and losers in different worlds.

Watts explains the research findings pretty concisely:

“The reason is that when people tend to like what other people like, differences in popularity are subject to what is called “cumulative advantage,” or the “rich get richer” effect. This means that if one object happens to be slightly more popular than another at just the right point, it will tend to become more popular still. As a result, even tiny, random fluctuations can blow up, generating potentially enormous long-run differences among even indistinguishable competitors — a phenomenon that is similar in some ways to the famous “butterfly effect” from chaos theory. Thus, if history were to be somehow rerun many times, seemingly identical universes with the same set of competitors and the same overall market tastes would quickly generate different winners...”

There are interesting implications here for social Information Architecture, and in particular the use of popularity-based navigation schemes. The first is that sensitivity to initial conditions plays a big role in what becomes popular. We can't know what will become popular, and even the patterns or indicators we identify in past events may be nothing more than wishful hindsight. As Watts puts it "just because we now know that something happened doesn’t imply that we could have known it was going to happen at the time, even in principle, because at the time, it wasn’t necessarily going to happen at all."

What this means for the social web - the links, songs, videos articles and photos that win out are not necessarily the best. Often they are ones that are liked by the first few users for some random reason (or by the Gather members that spam their entire social network saying "check out this new article I wrote") setting trends in place for later users. On the one hand, the web is democratic making it possible for anyone to participate. On the other hand, there network effects and other social phenomenon lead to the rich get richer effect and unpredictability in the system and making it harder for latecomers to have the same type of popularity.

For example, on sites like Digg, once a link has a certain number of diggs, it is likely to get dugg even more and reach the front page. On sites like YouTube viral sharing insures that the video that gets passed around some has a higher probability of getting passed around more ultimately leading to hits like LonelyGirl. One way to counteract this effect (though only to a small degree) is to give everyone a good starting point. For example, Gather does that on the front page by showing content chosen by their editorial staff, thus giving every uploaded article or picture a chance to gain some attention.

Surfacing random content in some other ways might be another way of reducing the rich get richer effect. Developing fancier algorithms like interestingness and using that to surface content might be another method. I am not sure how much of an impact that will have - after all interestingness does rely on the same type of social interactions - comments, favoriting, views etc. They have just been rolled together in an index that is less transparent than each of the individual components.

What are your thoughts? What are ways to counter the inevitable rich get richer effects? Does it need to be counteracted?

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Note: Will Evans is a software information architect for a risk modeling software company in Boston. Previously he was the information architect responsible for designing the Gather user experience (UX). He has published articles about Information Architecture, User Experience, and Interaction Design. He has taught User Centered Design and Building Usable Enterprise Architectures to both small and large corporate audiences.

He enjoys publishing his musings, ideas, poetry and pre-Simulationist critiques of modern culture, technology and aesthetics. He drinks way too much coffee and needs more sleep but is really trying to change that.