A Review on Models and Algorithms to Achieve Influence Maximization in Social Networks

Abstract

A major research problem in online social network is Influential node identification which has large number of ties in the network. Influence maximization finds an influential node and maximizes information diffusion. Organizations started to use information diffusion feature in marketing to improve their product promotion. To achieve influence maximization approximation algorithms and diffusion models are widely used. The existing methods consider degree and structure of the network in influential node identification. Most of the existing works consider number of nearest neighbors, user’s connectivity based on user’s rating. Influential nodes are mainly used in marketing and also used in various applications such as public opinion, healthcare, communication, education, agriculture, and epidemiology.