Mining multiplex interaction relationships from usage records in social networks

Social networks have become increasingly popular and are commonly used in everyday life. They also become the most convenient places to send information or receive advertisements. The multiplex network is an important study topic in social networks, in which many features could be appropriately represented in different layers. In this paper, we propose an approach to find the multiplex interaction relationships based on the action records of users on social networks. The multiplex user interactions are found and divided into three levels: high, normal and low. They are then used to check the friend and the follower relations such that users can find which friends or followers are active or not. In the experiments, the parameters are chosen based on Dunbar's number, which is the number of social relationships that humans can have with high confidence. The results show the proposed approach is effective in helping users know the truly close friend relationships on a social network.