Human activity in the web
Radicchi, FPhys. Rev. E 80, 026118 (2009)
Times cited: 43
Abstract
The recent information technology revolution has enabled the analysis
and processing of large-scale data sets describing human activities.
The main source of data is represented by the web, where humans
generally use to spend a relevant part of their day. Here, we study
three large data sets containing the information about web activities
of humans in different contexts. We study in details interevent and
waiting-time statistics. In both cases, the number of subsequent
operations which differs by tau units of time decays powerlike as tau
increases. We use nonparametric statistical tests in order to estimate
the significance level of reliability of global distributions to
describe activity patterns of single users. Global interevent time
probability distributions are not representative for the behavior of
single users: the shape of single users’ interevent distributions is
strongly influenced by the total number of operations performed by the
users and distributions of the total number of operations performed by
users are heterogeneous. A universal behavior can be anyway found by
suppressing the intrinsic dependence of the global probability
distribution on the activity of the users. This suppression can be
performed by simply dividing the interevent times with their average
values. Differently, waiting-time probability distributions seem to be
independent of the activity of users and global probability
distributions are able to significantly represent the replying activity
patterns of single users.