"Can We Detect Substance Use Disorder?": Knowledge and Time Aware Classification on Social Media from Darkweb

no code implementations • 20 Apr 2023 • Usha Lokala, Orchid Chetia Phukan, Triyasha Ghosh Dastidar, Francois Lamy, Raminta Daniulaityte, Amit Sheth

We use the Drug Abuse Ontology, state-of-the-art deep learning, and knowledge-aware BERT-based models to generate sentiment and emotion for the social media posts to understand users' perceptions on social media by investigating questions such as: which synthetic opioids people are optimistic, neutral, or negative about?

eDarkTrends: Harnessing Social Media Trends in Substance use disorders for Opioid Listings on Cryptomarket

no code implementations • 29 Mar 2021 • Usha Lokala, Francois Lamy, Triyasha Ghosh Dastidar, Kaushik Roy, Raminta Daniulaityte, Srinivasan Parthasarathy, Amit Sheth

However, the lack of evidence on the relationship has resulted in opioids being largely inaccessible through legal means.

"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware Attention Framework for Relationship Extraction

no code implementations • 21 Sep 2020 • Shweta Yadav, Usha Lokala, Raminta Daniulaityte, Krishnaprasad Thirunarayan, Francois Lamy, Amit Sheth

In this interdisciplinary study, we demonstrate the value of incorporating domain-specific knowledge in the learning process to identify the relationships between cannabis use and depression.

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