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Distance-Aware Influence Maximization Algorithm based on Random Walk

Abstract— In this paper, we investigate the distance-aware influence maximization problem on the independent cascade(IC) model. A random walk based algorithm is presented to find the seed set to maximizing the influence for a distance aware query. Random walk method is used to perform path sampling to simulate the influence propagation process. Based on the result using random walk method, greedy method is used to select the seed set. Our experimental results show that the algorithm can reasonably select the seed set to maximize the influence propagation.

Index Terms— Influence maximization, Distance-aware, Random walk, Greedy method

Yuwei Wang
Department of Computer Science, Yangzhou University, Yangzhou,CHINA
Ling Chen
State Key Lab of Novel Software Tech, Nanjing University, Nanjing, CHINA

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Cite: Yuwei Wang, Ling Chen, "Distance-Aware Influence Maximization Algorithm based on Random Walk," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering, pp. 807-814, Hong Kong, 15-17 June, 2019.