Summary
Asia-Pacific Network Operations and Management Symposium
2019
Session Number:TS5
Session:
Number:TS5-1
Susceptible-Infection-based Cost-effective Seed Mining in Social Networks
Ashis Talukder, Choong Seon Hong,
pp.-
Publication Date:2019/9/18
Online ISSN:2188-5079
Summary:
The aim of Influence maximization (IM) techniques is to mine social networks to find a small set of influential seed users that maximize the viral marketing profit. On the other hand, the Reverse Influence Maximization (RIM) maximizes the profit by minimizing the viral marketing cost. Here, the cost is estimated by the lowest number of nodes which are needed to activate seed nodes. On the other hand, the profit is computed by the highest number of nodes that can be influenced by seed users. However, most of the existing works assume that the seed nodes are either initially activated or offered free products for motivation. Thus, most of the studies do not address the seed activation cost. Therefore, in this research, we propose a Susceptible-Infection-based Greedy Reverse Influence Maximization (SIG-RIM) model to maximize the profit by minimizing the seeding cost. The proposed SIG-RIM model employs the Susceptible-Infected (SI) mechanism in reverse order to compute the seeding cost and a greedy technique to optimize the cost. Moreover, the SIG-RIM model tackles RIM challenges more efficiently. Finally, we conduct the performance evaluation of our model with real datasets of two popular social networks, and the result shows that the proposed model outperforms state-of-the-art models.