Frequent Pattern Mining in Social Network Data (Facebook Application Data)
Data Mining is a process, which involves identification of useful patterns and gathers knowledge which was hidden earlier. It involves various processes of which classification, association rule mining and clustering gain major attention. One of the emerging application areas of Data Mining is Social Networks. In this paper, the authors highlight the significance of mining patterns in Social Network data. The Dataset used in this paper is Facebook Application installation/usage Dataset which contains details of installation of nearly 16,800 applications among 3,00,000 users. As the dataset is voluminous, the work begins with Data Preprocessing where dataset is divided into subsets based on the number of applications installed/used.