Researchers at the University of Michigan published a novel study this week, called ‘Social Influence and the Diffusion of User Created Content’ looking at how social influence works through social networking. The study was funded by the National Science Foundation and looked to take advantage of the new cyber trail that our online transactions leave behind.
They looked at Second Life, the virtual-world social network which has the capacity for users to share and adopt each others gestures and behaviours. The researchers looked only at gestures (otherwise known as assets) which are simple to produce, freely available and widely distributed. These assets may include dance moves, laughs and claps that the virtual you can perform. Overall they studied data concerning 100,229 users and 106,499 assets, between September 2008 and January 2009.
It is possible for users to buy such assets from online stores but the researchers found that 48% of assets transferred were distributed between ’friends’. Friends are described as ‘users with a reciprocated permission to see each others online status’, though I don’t think this definition of friendship will make it into any greetings cards.
It almost goes without saying that everyone should be extremely cautious about extrapolating this study but there is something undeniably fascinating about the level of detail that the researchers could investigate. They had precise information about when and where each asset was transferred; something almost impossible to pin down in the real world.
The researchers suggest that early adopters of assets are not the same as influencers – people responsible for passing on a lot of assets. They also report that the number of ’friends’ one has is not a significant predictor of adoption influence. Now these are not revolutionary findings and are fairly intuitive but what intrigues me is how we, and marketing strategists, look at the distribution of behaviours.
On your homepage, Facebook details the things your friends are signing up to and becoming fans of. This seems to be a reaction to this type of research and something that will evolve and increase as the data trail becomes more explicit. To understand further how a cat puppet playing a keyboard becomes an internet sensation or a phrase becomes a meme, this type of social research is important. The frustration implicit in translating online research to the ‘real world’ is placated by our ability to see unprecedented details about how these things are transferred. The researchers in this paper sometimes described the distribution of behaviours as analogous to the spread of a virus and whilst this is not something anyone will be rushing to cure, studying it will shape the viral pathways of the future.