Frequent Pattern Mining Method to Influence Social Network Users for Marketing in an Efficient Way

Social networks have become an important marketing tools for business to build brand pages to prompt their new products. If this medium is explored intelligently then the social network medium has a potential to provide many new ways to market the audience with the help of registered users indirectly, without knowing them. Social Network (Face book) has provided many tools for marketing purpose like groups, events, social ads. 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. When analyzing the users’ scope of social networking, it can be concluded that the modern social communities influence in individual’s private life. 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. It also presents a survey based research from users and organizations for finding their views on the tagged based marketing on the social networking website 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, helps in understanding the reason what are the barriers and what steps could be taken to make it effective for organizations, 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. Keywords-Social network mining; frequent i t e m set; Social network influence; Marketing on social Network; Tagged Based