  With the widespread use of mobile computing devices in contemporary society,
our trajectories in the physical space and virtual world are increasingly
closely connected. Using the anonymous smartphone data of $1 \times 10^5$ users
in 30 days, we constructed the mobility network and the attention network to
study the correlations between online and offline human behaviours. In the
mobility network, nodes are physical locations and edges represent the
movements between locations, and in the attention network, nodes are websites
and edges represent the switch of users between websites. We apply the
box-covering method to renormalise the networks. The investigated network
properties include the size of box $l_B$ and the number of boxes $N(l_B)$. We
find two universal classes of behaviours: the mobility network is featured by a
small-world property, $N(l_B) \simeq e^{-l_B}$, whereas the attention network
is characterised by a self-similar property $N(l_B) \simeq l_B^{-\gamma}$. In
particular, with the increasing of the length of box $l_B$, the degree
correlation of the network changes from positive to negative which indicates
that there are two layers of structure in the mobility network. We use the
results of network renormalisation to detect the community and map the
structure of the mobility network. Further, we located the most relevant
websites visited in these communities, and identified three typical
location-based behaviours, including the shopping, dating, and taxi-calling.
Finally, we offered a revised geometric network model to explain our findings
in the perspective of spatial-constrained attachment.
