Abdulaziz Alhamadani, Shailik Sarkar, Lulwah AlKulaib


The drug abuse epidemic has been on the rise in the past few years, particularly after the start of COVID-19 pandemic. Our preliminary observations on Reddit alone show that discussions on drugs from 2018 to 2020 increased between a range of 45% to 200%, and so has the number of unique users participating in those discussions. Existing efforts focused on utilizing social media to distinguish potential drug abuse chats from unharmful chats regardless of what drug is being abused. Others focused on understanding the trends and causes of drug abuse from social media. To this end, we introduce PRISTINE (opioid crisis detection on reddit), our work dynamically detects-and extracts evolving misleading drug names from Reddit comments using reinforced Dynamic Query Expansion (DQE) and constructs a textual Graph Convolutional Network with the aid of powerful pre-trained embeddings to detect which type of drug class a Reddit comment corresponds to. Further, we perform extensive experiments to investigate the effectiveness of our model.

Abdulaziz Alhamadani, Shailik Sarkar, Lulwah Alkulaib, Chang-Tien Lu: PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit. ASONAM 2022: 444-453


Publication Details

Date of publication:
March 23, 2023
IEEE/ACM Advances in Social Networks Analysis and Mining (ASONAM)
Page number(s):