Stability and Robustness in Influence Maximization

Abstract

In the well-studied Influence Maximization problem, the goal is to identify a set of k nodes in a social network whose joint influence on the network is maximized. A large body of recent work has justified research on Influence Maximization models and algorithms with their potential to create societal or economic value. However, in order to live up to this potential, the algorithms must be robust to large amounts of noise, for they require quantitative estimates of the influence, which individuals exert on each other; ground truth for such quantities is inaccessible, and even decent estimates are very difficult to obtain.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 31, 2018
Source ID
10.1145/3233227

Entities

People

  • David Kempe
  • Xinran He

Organizations

  • Defense Advanced Research Projects Agency
  • National Science Foundation
  • University of Southern California

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Systems Analysis and Design
  • Theoretical Analysis.