An Efficient Graph Eccentric Approach to find Influential Nodes in Social Network

The advent of technology has enhanced the marketing approaches. Today the best platform for marketing is social network, but the question arises, to whom we should share the content to spread it across. Our work focuses, to find the most influential member (node) in a social network. The societal needs have made network centric computing significant. The internet research community such as promoting sales, viral marketing and campaigning has focused their attention on effective utilization of social network platforms. In marketing era it is difficult to find the influential member to introduce any product. In this paper we propose a better solution to find top-k nodes by using the concept of graph theory. Our method gives the solution to 1) Finding the centrality based on number of connections. 2) To find the minimal count of nodes to traverse maximum network. 3) λ-coverage problem to calculate maximum number of nodes needed to cover λ percentage of area. The result shows our method gives significant output.