  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.
