Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10321911 | Expert Systems with Applications | 2015 | 23 Pages |
Abstract
Finding the most influential people is an NP-hard problem that has attracted many researchers in the field of social networks. The problem is also known as influence maximization and aims to find a number of people that are able to maximize the spread of influence through a target social network. In this paper, a new algorithm based on the linear threshold model of influence maximization is proposed. The main benefit of the algorithm is that it reduces the number of investigated nodes without loss of quality to decrease its execution time. Our experimental results based on two well-known datasets show that the proposed algorithm is much faster and at the same time more efficient than the state of the art algorithms.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Khadije Rahimkhani, Abolfazl Aleahmad, Maseud Rahgozar, Ali Moeini,