  We investigate transitions of portals users between different subpages. A
weighted network of portals subpages is reconstructed where edge weights are
numbers of corresponding transitions. Distributions of link weights and node
strengths follow power laws over several decades. Node strength increases
faster than linearly with node degree. The distribution of time spent by the
user at one subpage decays as power law with exponent around 1.3. Distribution
of numbers P(z) of unique subpages during one visit is exponential. We find a
square root dependence between the average z and the total number of
transitions n during a single visit. Individual path of portal user resembles
of self-attracting walk on the weighted network. Analytical model is developed
to recover in part the collected data.
