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Found 6 papers, 1 papers with code
Predictive Analysis on Twitter: Techniques and Applications
Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide.
Social and Information Networks
"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware Attention Framework for Relationship Extraction
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.
"Is depression related to cannabis?": A knowledge-infused model for Entity and Relation Extraction with Limited Supervision
With strong marketing advocacy of the benefits of cannabis use for improved mental health, cannabis legalization is a priority among legislators.
eDarkTrends: Harnessing Social Media Trends in Substance use disorders for Opioid Listings on Cryptomarket
However, the lack of evidence on the relationship has resulted in opioids being largely inaccessible through legal means.
A Computational Approach to Understand Mental Health from Reddit: Knowledge-aware Multitask Learning Framework
We collect a corpus of $150k$ items (posts and comments) annotated using the subreddit labels and transfer learning approaches.
"Can We Detect Substance Use Disorder?": Knowledge and Time Aware Classification on Social Media from Darkweb
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?
