Abstract:
Social Network Analysis (SNA) is a technique for modeling the communication patterns between individuals in a way that illuminates the structure of the network and the importance of individuals within the network. SNA has gained a recent importance due to the appearance of various web 2.0 platforms like blogs, wikis, content and media sharing sites which consists of a huge collection of data. These data are vast, noisy, unstructured and dynamic in nature, so mining is performed on such data by various SNA methods and tools in order to extract actionable patterns which are useful for business, consumers, and users. This study is a part of the growing body of research on Social Network Analysis and uncovers hidden relationships in a facebook network. It gives a prospective view of the hidden attributes of the high degree nodes (users having greater number of friends) in the Facebook network. Results show that there is little association among high degree nodes.