Influence Maximization on Social Networks: A Study

Title:Influence Maximization on Social Networks: A Study

Volume: 14 Issue: 1

Author(s): Shashank S. Singh*, Kuldeep Singh, Ajay Kumar and Bhaskar Biswas

Affiliation:

• Department of Computer Science and Engineering, Bennett University, Greater Noida, Uttar Pradesh,India

Keywords: Influence maximization, social networks, information diffusion, viral marketing, profit maximization, revenue maximization.

Abstract: Influence Maximization, which selects a set of k users (called seed set) from a social network to maximize the expected number of influenced users (called influence spread), is a key algorithmic problem in social influence analysis. In this paper, we give recent studies on influence maximization algorithms. The main goal of this survey is to provide recent studies and future research opportunities. We give taxonomy of influence maximization algorithms with the comparative theoretical analysis. This paper provides a theoretical analysis of influence maximization problem based on algorithm design perspective and also provides the performance analysis of existing algorithms.

Cite this article as:

Singh S. Shashank *, Singh Kuldeep , Kumar Ajay and Biswas Bhaskar , Influence Maximization on Social Networks: A Study, Recent Advances in Computer Science and Communications 2021; 14 (1) . https://dx.doi.org/10.2174/2213275912666190417152547