Influence Maximization for Social Network Based Substance Abuse Prevention

Aida Rahmattalabi, Anamika Barman-Adhikari, Phebe Vayanos, Milind Tambe, Eric Rice, Robin Baker

AAAI 2018 pp. 8139-8140

doi:10.1609/AAAI.V32I1.12196 /aaai/2018/rahmattalabi2018aaai-influence/

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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Text

Rahmattalabi et al. "Influence Maximization for Social Network Based Substance Abuse Prevention." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12196

Markdown

[Rahmattalabi et al. "Influence Maximization for Social Network Based Substance Abuse Prevention." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/rahmattalabi2018aaai-influence/) doi:10.1609/AAAI.V32I1.12196

BibTeX

@inproceedings{rahmattalabi2018aaai-influence,
  title     = {{Influence Maximization for Social Network Based Substance Abuse Prevention}},
  author    = {Rahmattalabi, Aida and Barman-Adhikari, Anamika and Vayanos, Phebe and Tambe, Milind and Rice, Eric and Baker, Robin},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8139-8140},
  doi       = {10.1609/AAAI.V32I1.12196},
  url       = {https://mlanthology.org/aaai/2018/rahmattalabi2018aaai-influence/}
}