Influence maximization in social networks: a survey of behaviour-aware methods

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