Uncharted but not uninfluenced: Influence maximization with an uncertain network
This paper focuses on new challenges in influence maximization inspired by non-profits' use of social networks to effect behavioral change in their target populations. Influence maximization is a mul-tiagent problem where the challenge is to select the most influential agents from a population connected by a social network. Specifically, our work is motivated by the problem of spreading messages about HIV prevention among homeless youth using their social network. We show how to compute solutions which are provably close to optimal when the parameters of the influence process are unknown. We then extend our algorithm to a dynamic setting where information about the network is revealed at each stage. Simulation experiments using real world networks collected by the homeless shelter show the advantages of our approach.
Files
Metadata
| Work Title | Uncharted but not uninfluenced: Influence maximization with an uncertain network |
|---|---|
| Access | |
| Creators |
|
| License | In Copyright (Rights Reserved) |
| Work Type | Article |
| Publication Date | January 1, 2017 |
| Deposited | March 12, 2025 |
Versions
Analytics
Collections
This resource is currently not in any collection.