PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit
14th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022
; : 444-453, 2022.
Article
in English
| Scopus | ID: covidwho-2290980
ABSTRACT
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. © 2022 IEEE.
detection; drug abuse epidemic; dynamic query expansion; graph convolutional network; social media data mining; word embeddings; Convolution; Convolutional neural networks; COVID-19; Data mining; Deep learning; Expansion; Query processing; Social networking (online); Convolutional networks; Drug abuse; Dynamic query expansions; Embeddings; Opioids; Social media data minings; Word embedding
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022
Year:
2022
Document Type:
Article
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