Document Type
Article
Publication Date
5-18-2017
Publication Title
Computational Social Networks
Abstract
Merging two classic questions
The influence-maximization literature seeks small sets of individuals whose structural placement in the social network can drive large cascades of behavior. Optimization efforts to find the best seed set often assume perfect knowledge of the network topology. Unfortunately, social network links are rarely known in an exact way. When do seeding strategies based on less-than-accurate link prediction provide valuable insight?
Keywords
Influence maximization, Link prediction, Threshold spread, Network seeding, Optimization under uncertainty
Volume
4
Issue
1
DOI
DOI 10.1186/s40649-017-0037-3
Rights
© The Author(s) 2017
Recommended Citation
Wei, Yijin and Spencer, Gwen, "Measuring the Value of Accurate Link Prediction for Network Seeding" (2017). Mathematics Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/mth_facpubs/30
Comments
Archived as published.