  All online sharing systems gather data that reflects users' collective
behaviour and their shared activities. This data can be used to extract
different kinds of relationships, which can be grouped into layers, and which
are basic components of the multidimensional social network proposed in the
paper. The layers are created on the basis of two types of relations between
humans, i.e. direct and object-based ones which respectively correspond to
either social or semantic links between individuals. For better understanding
of the complexity of the social network structure, layers and their profiles
were identified and studied on two, spanned in time, snapshots of the Flickr
population. Additionally, for each layer, a separate strength measure was
proposed. The experiments on the Flickr photo sharing system revealed that the
relationships between users result either from semantic links between objects
they operate on or from social connections of these users. Moreover, the
density of the social network increases in time. The second part of the study
is devoted to building a social recommender system that supports the creation
of new relations between users in a multimedia sharing system. Its main goal is
to generate personalized suggestions that are continuously adapted to users'
needs depending on the personal weights assigned to each layer in the
multidimensional social network. The conducted experiments confirmed the
usefulness of the proposed model.
