A Multi-objective Algorithm for Identifying Influential Nodes in Social Networks

With the expansion of social networks, relationship between people has taken a new form. One of the important issues in social networks is social influence. Research on social influences and how information is disseminated in social networks, indicates that accepting or rejecting a new pattern by a person depends on the acceptance or rejection of the friends of that person. That is, because the people usually trust their friends more than other sources of advertising. As a result, many companies are focused on this type of advertisement which is called viral marketing. Given a large number of users in a social network, selecting the most influential users as target users, through which a company can reach the highest expansion in the network with the lowest cost, is of great importance. In this paper, a new method for identifying the influential nodes in social networks is proposed which is called MOSI (Multi-Objective algorithm based on Structured Information). The proposed method has two goals: "maximize profit" and "minimize similarity among selected users". The evaluation of the proposed method on real datasets indicates that our method has a greater expansion power in comparison with other similar methods.