Influence Maximization for Social Network Based Substance Abuse Prevention

Authors

  • Aida Rahmattalabi University of Southern California
  • Anamika Barman Adhikari University of Denver
  • Phebe Vayanos University of Southern California
  • Milind Tambe University of Southern California
  • Eric Rice University of Southern California
  • Robin Baker Urban Peak Organization

Keywords:

AI, Substance Abuse, Social Good, Algorithms

Abstract

Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of reducing substance abuse. While effective, inappropriate intervention groups can result in an increase in deviant behaviors among participants, a process known as deviancy training. In this paper, we present GUIDE, an AI-based decision aid that leverages social network information to optimize the structure of the intervention groups.

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Published

2018-04-29

How to Cite

Rahmattalabi, A., Barman Adhikari, A., Vayanos, P., Tambe, M., Rice, E., & Baker, R. (2018). Influence Maximization for Social Network Based Substance Abuse Prevention. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/12196