Human Activity in the Web TeX Export

@article{citeulike:4191818, abstract = {The recent information technology revolution has enabled the analysis and processing of large-scale datasets 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 datasets containing the information about Web human activities in different contexts. We study in details inter-event and waiting time statistics. In both cases, the number of subsequent operations which differ by \$\tau\$ units of time decays power-like as \$\tau\$ increases. We use non-parametric statistical tests in order to estimate the significance level of reliability of global distributions to describe activity patterns of single users. Global inter-event time probability distributions are not representative for the behavior of single users: decay exponents of single users'inter-event distributions are 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. 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.}, archivePrefix = {arXiv}, author = {Radicchi, Filippo}, citeulike-article-id = {4191818}, citeulike-linkout-0 = {http://arxiv.org/abs/0903.2999}, citeulike-linkout-1 = {http://arxiv.org/pdf/0903.2999}, day = {17}, eprint = {0903.2999}, keywords = {activity, human, in, the, web}, month = {Mar}, posted-at = {2009-03-19 21:16:11}, priority = {2}, title = {Human Activity in the Web}, url = {http://arxiv.org/abs/0903.2999}, year = {2009} }

TY - JOUR ID - citeulike:4191818 L3 - citeulike-article-id:4191818 N2 - The recent information technology revolution has enabled the analysis and processing of large-scale datasets 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 datasets containing the information about Web human activities in different contexts. We study in details inter-event and waiting time statistics. In both cases, the number of subsequent operations which differ by $\tau$ units of time decays power-like as $\tau$ increases. We use non-parametric statistical tests in order to estimate the significance level of reliability of global distributions to describe activity patterns of single users. Global inter-event time probability distributions are not representative for the behavior of single users: decay exponents of single users'inter-event distributions are 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. 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. TI - Human Activity in the Web KW - activity KW - human KW - in KW - the KW - web AU - Radicchi, Filippo PY - 2009/Mar/17/ UR - http://arxiv.org/abs/0903.2999 ER -