  Opioid and substance misuse is rampant in the United States today, with the
phenomenon known as the opioid crisis. The relationship between substance use
and mental health has been extensively studied, with one possible relationship
being substance misuse causes poor mental health. However, the lack of evidence
on the relationship has resulted in opioids being largely inaccessible through
legal means. This study analyzes the substance misuse posts on social media
with the opioids being sold through crypto market listings. We use the Drug
Abuse Ontology, state-of-the-art deep learning, and BERT-based models to
generate sentiment and emotion for the social media posts to understand user
perception on social media by investigating questions such as, which synthetic
opioids people are optimistic, neutral, or negative about or what kind of drugs
induced fear and sorrow or what kind of drugs people love or thankful about or
which drug people think negatively about or which opioids cause little to no
sentimental reaction. We also perform topic analysis associated with the
generated sentiments and emotions to understand which topics correlate with
people's responses to various drugs. Our findings can help shape policy to help
isolate opioid use cases where timely intervention may be required to prevent
adverse consequences, prevent overdose-related deaths, and worsen the epidemic.
