mlsanityData to 14 Oct 2026

A Survey on Location-Driven Influence Maximization

arXiv 2204.08005 ↗First posted 17 Apr 2022cs.SI cs.GTcited by 3

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Abstract (arXiv)

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its research outcomes significantly impact real-world applications such as business marketing. The booming location-based network platforms of the last decade appeal to the researchers embedding the location information into traditional IM research. In this survey, we provide a comprehensive review of the existing location-driven IM studies from the perspective of the following key aspects: (1) a review of the application scenarios of these works, (2) the diffusion models to evaluate the influence propagation, and (3) a comprehensive study of the approaches to deal with the location-driven IM problems together with a particular focus on the accelerating techniques. In the end, we draw prospects into the research directions in future IM research.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Apr 2022.

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Citing papers per year: 2022: 1; 2023: 1; 2024: 1.

3 papers.