Preference aware influence maximization

Authors

Changbo Jiang, Changsha University of Science And TechnologyFollow
Weihua Li, University of WollongongFollow
Quan Bai, Auckland University of TechnologyFollow
Minjie Zhang, University of WollongongFollow

RIS ID

111139

Publication Details

Jiang, C., Li, W., Bai, Q. & Zhang, M. (2017). Preference aware influence maximization. Studies in Computational Intelligence, 670 153-164.

Abstract

With the development of social network, online marketing has become more popular and developed in an unprecedented scale. Viral marketing propagates influence through ‘word-of-mouth’ effect. As for development of viral marketing, it is critical to select a set of influential users in the network to propagate influence as much as possible with limited resources. In this chapter, we proposed a model called Preference-based Trust Independent Cascade Model. Based on the experimental results, the Preference-based Trust Independent Cascade Model is able to obtain better results than some traditional models. Comparing with other existing methods, such as trust-only approach and random selection approach, the proposed Preference-based Trust Independent Cascade Model considers both user preference and trust connectivity.