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Target-aware holistic influence maximization in spatial social networks

journal contribution
posted on 2020-01-01, 00:00 authored by TaoTao Cai, Jianxin LiJianxin Li, Ajmal S Mian, Ronghua li, Timos Sellis, Jeffrey Xu Yu
Influence maximization has recently received significant attention for scheduling online campaigns or advertisements on social network platforms. However, most studies only focus on user influence via cyber interactions while ignoring their physical interactions which are also essential to gauge influence propagation. Additionally, targeted campaigns or advertisements have not received sufficient attention. To address these issues, we first devise a novel holistic influence diffusion model that takes into account both cyber and physical user interactions in an effective and practical way. Based on the new diffusion model, we formulate a new problem of holistic influence maximization, denoted as HIM query, for targeted advertisements in a spatial social network. The HIM query problem aims to find a minimum set of users whose holistic influence can cover all target users in the network, which belongs to a set covering problem. Since the HIM query problem is NP-hard, we develop a greedy baseline algorithm and then improve on this algorithm to reduce the computational cost. To deal with large networks, we also design a spatial-social index to maintain the social, spatial and textual information of users, as well as developing an index-based efficient solution. Finally, we conduct extensive experiments to validate the efficiency and effectiveness of the proposed diffusion model and developed algorithms.

History

Journal

IEEE transactions on knowledge and data engineering

Pagination

1 - 14

Publisher

Institute of Electrical and Electronics Engineers

ISSN

1041-4347

eISSN

2326-3865

Language

eng

Publication classification

C1 Refereed article in a scholarly journal