Mining Influential Users in Social Network

Social networks have become an important marketing tools for business to build brand pages to prompt their new products. Fans´ user-experience diffusion results in great marketing power that people never seen. Typically, some of the fans in group are influence users. They are market movers which mean they can influence others buying decisions. Businesses can affect online influence users by giving them extra benefits to turn them into spokesmen. However, who is the influential user? What period of time is appropriate for information to spread? In this study, a framework based on frequent pattern mining is proposed to find the influence users as well as the proper time to spread information. The one day 24-hour period can be divided into successive time segments. An influence transaction that contains fans´ influence power will be defined in each time segment. After transactions being collected several days, the frequent patterns can be found to deduce the proper time for influence users to spread information. The theoretical experiment is given to show how the proposed framework works.