Researchers from the University of Limerick, University of Oxford and the Harvard School of Public Health developed a mathematical model to examine online social networks.
The researchers found that users selected apps on the basis of recent adoptions by their friends rather than by using Facebook’s equivalent of a bestseller list of apps.
The research, published in the journal, Proceedings of the National Academy of Sciences, found that the “copycat” tendency in human behaviour is strong and that we can be influenced by the activities of others over a relatively short period of time.
Professor James Gleeson, of UL’s mathematics and statistics department said: “This study reveals how we can explore different scenarios using mathematical models to disentangle what drives people to behave the way they do, using large data sets from the real, online world. This opens up lots of new possibilities for studying human behaviour.”
The researchers examined data from an empirical study published in 2010, which had tracked 100 million installations of apps adopted by Facebook users during two months.
In the 2010 study (which included two of the authors of the new study), researchers found that in some cases, a user’s decision to install some apps seemed virtually unaffected by the activities of others, whereas sometimes they were strongly affected by the behaviour of others — even though the apps in these two categories did not appear to be distinguished by any particular characteristics.
Instead, once an app reached some popularity threshold (as measured by the installation rate), its popularity tended to rise to stellar proportions.
In the new study, the researchers developed a mathematical model to distinguish between the consequences of two distinct, competing mechanisms that appeared to drive the dynamics behind the behaviour of the Facebook users.
Using the supercomputers of the Irish Centre for High-End Computing (ICHEC), the researchers ran thousands of simulations in which they varied the relative dominance of the two influences (recent installations versus cumulative popularity).
It took the researchers 15,000 hours of computer processing to best match the results of the simulations with the characteristics of app installation that were observed in the earlier empirical study.
The researchers found that, although Facebook users seem to be influenced by both, the stronger effect on popularity dynamics was caused by the recent behaviour of others.