Duncan Watts (author of Six Degrees) wrote an article in the New York Times about the rich get richer effect (via). 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. 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.
What this means for the social web – the links, songs, videos and slideshows that win out are not necessarily the best. Often they are ones that are liked by the first few users for some random reason, 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, we do that on SlideShare by showing the “Latest” slideshow on the front page, thus giving every uploaded slideshow a change to gain some attention.
Surfacing random content in some other ways might be another way of reducing the rich get richer effect. Gene hypothesizes that 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?