Exploiting viral marketing for location promotion in location-based social networks

Wen Yuan Zhu, Wen Chih Peng, Ling Jyh Chen, Kai Zheng, Xiaofang Zhou

研究成果: 雜誌貢獻期刊論文同行評審

17 引文 斯高帕斯(Scopus)


With the explosion of smartphones and social network services, location-based social networks (LBSNs) are increasingly seen as tools for businesses (e.g., restaurants and hotels) to promote their products and services. In this article, we investigate the key techniques that can help businesses promote their locations by advertising wisely through the underlying LBSNs. In order to maximize the benefit of location promotion, we formalize it as an influence maximization problem in an LBSN, i.e., given a target location and an LBSN, a set of k users (called seeds) should be advertised initially such that they can successfully propagate and attract many other users to visit the target location. Existing studies have proposed different ways to calculate the information propagation probability, that is, how likely it is that a user may influence another, in the setting of a static social network. However, it is more challenging to derive the propagation probability in an LBSN since it is heavily affected by the target location and the user mobility, both of which are dynamic and query dependent. This article proposes two user mobility models, namely the Gaussian-based and distance-based mobility models, to capture the check-in behavior of individual LBSN users, based on which location-aware propagation probabilities can be derived. Extensive experiments based on two real LBSN datasets have demonstrated the superior effectiveness of our proposals compared with existing static models of propagation probabilities to truly reflect the information propagation in LBSNs.

期刊ACM Transactions on Knowledge Discovery from Data
出版狀態已發佈 - 2016 11月

ASJC Scopus subject areas

  • 一般電腦科學


深入研究「Exploiting viral marketing for location promotion in location-based social networks」主題。共同形成了獨特的指紋。