  Social networks have become an increasingly common abstraction to capture the
interactions of individual users in a number of everyday activities and
applications. As a result, the analysis of such networks has attracted lots of
attention in the literature. Among the topics of interest, a key problem
relates to identifying so-called influential users for a number of
applications, which need to spread messages. Several approaches have been
proposed to estimate users' influence and identify sets of influential users in
social networks. A common basis of these approaches is to consider links
between users, that is, structural or topological properties of the network. To
a lesser extent, some approaches take into account users' behaviours or
attitudes. Although a number of surveys have reviewed approaches based on
structural properties of social networks, there has been no comprehensive
review of approaches that take into account users' behaviour. This paper
attempts to cover this gap by reviewing and proposing a taxonomy of such
behaviour-aware methods to identify influential users in social networks.

Social and Information Networks