A Survey on Detecting Influential User in Social Networking

Due to the spread of technology, Online Social Media has invaded every home in the world. One of the most interesting fields of study in social network analysis is to identify influential users who express and share their point of view on particular and critical topics to their audiences and gain their trust. The goal behind this identification is the effective information dissemination or even controlling the spread. This paper provides a systematic analysis of various existing techniques and methods used for influential node detection like bipartite networks using SVD-rank and SVDA-rank Algorithms, by using Gaussian kernel method and grey wolf optimization method. In the gaussian kernel method, positive and negative signs indicated whether the user was an influential user or not. In the grey wolf optimization method, an optimal solution was obtained using wolves-like parameters. It has been observed that with the passage of time, researchers modify the techniques which yield better results with higher accuracy than before. Thus, this paper does a quick survey of the various studies done by the researchers in recent years in this area with different techniques.