Substance abuse, or also known as drug abuse, is the use of a drug in a larger amount than prescribed, or more frequently than needed or necessary.
For most people, drug abuse is just another way for them to alter their consciousness in the form of recreational activities. Other abuse drugs after developing more compulsive drug-using patterns, and the rest may abuse drugs in order to fulfill other purposes, like to help them enhance identity, acceptance, and reducing psychological distress or a sense of alienation.
The thing is, many people don't understand why or how other people become addicted to drugs. They may mistakenly think that drug abusers are people who lack the moral principles or willpower, and that they could stop their drug use simply by choosing to.
Because the exact cause of drug abuse is not clear, theories can suggest that people abuse substances after learning it from others, or after developing the habit after addiction developed.
This is why drug abuse and drug addiction is a complex disease, and quitting usually takes more than good intentions or a strong will.
While the relationship between mental health and drug abuse is well-studied in clinical environments, but the way people discuss and interact with one another in the real world regarding drugs is beyond the realm of most scientific studies.
This is why an international team of researchers try to put together the many pieces of information that haven't been thoroughly studies before, in order to better understand the minds of drug abusers.
To do this, they developed an AI system, which learns from data gathered from three popular cryptomarkets on the dark web, where drugs are sold in order to determine nuanced information about what people were searching for and purchasing.
After that, the researchers crawled popular drug-related subreddits on social news aggregation Reddit, such as r/opiates and r/drugnerds for posts related to the cryptomarket terminology in order to gather emotional sentiment. The researchers then crawled various hashtags on the microblogging platform Twitter to find some easy-to-label emotional sentiments.
The goal isn't to track sales or the expose users.
Instead, it's to better understand how drug abusers feel and what terms they’re using to describe their experiences while on drugs.
According to the team’s research paper:
In this study, we assess social media data from active opioid users to understand what are the behaviors associated with opioid usage to identify what types of feelings are expressed. We employ deep learning models to perform sentiment and emotion analysis of social media data with the drug entities derived from cryptomarkets.
The result is a massive trove of data, that allowed the team to determine a robust emotional sentiment analysis for various substances.
In the future, the team hopes to find a way to gain better access to dark web cryptomarkets in order to create stronger sentiment models. The ultimate goal of the project is to help healthcare professionals better understand the relationship between mental health and substance abuse.
"To identify the best strategies to reduce opioid misuse, a better understanding of cryptomarket drug sales that impact consumption and how it reflects social media discussions is needed," the researchers wrote.
