Related Experiment Video
Updated: Jul 13, 2026
07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Modeling multidimensional perceived risk in HIV-related social media: a multi-label transformers framework with
Abdollah Abadian1, Abdullah1,2, Zulaikha Fatima3
1Center for Computing Research, Instituto Politecnico Nacional (IPN), Mexico City, 07320, Mexico.
Scientific Reports
|July 11, 2026
Summary
This study developed a machine learning model to analyze perceived risks in online HIV/AIDS discussions. The model identified increasing transmission and health risks, and highlighted the connection between transmission and social stigma.
Area of Science:
- Computational Linguistics
- Public Health Informatics
- Social Computing
Background:
- Online communities like Reddit are vital for HIV/AIDS discourse.
- Understanding user-perceived risks is crucial for public health interventions.
- Previous analyses lacked scalability and multidimensional risk detection.
Purpose of the Study:
- To develop and validate a supervised multi-label framework for detecting multidimensional perceived risk in HIV-related online discourse.
- To analyze trends and patterns in perceived HIV risks over time.
- To assess the utility of transformer-based models for analyzing health perceptions in online communities.
Main Methods:
- A longitudinal corpus of 329,707 Reddit posts from r/hivaids and r/HIV (2015-2025) was analyzed.
- A stratified sample of 2,000 texts was annotated by domain experts for transmission risk, health deterioration risk, and social stigma risk.
- A RoBERTa-base model was fine-tuned for multi-label classification, outperforming 12 baseline models.
Main Results:
- The RoBERTa-base model achieved a macro-F1 score of 0.87 and macro-AUC-ROC of 0.97.
- Significant upward trends in transmission and health deterioration risks were observed.
- Strong co-occurrence between transmission and stigma discourse, and distinct information-seeking patterns emerged.
Conclusions:
- Transformer-based multi-label learning offers a scalable and reproducible method for analyzing HIV-related health perceptions.
- Findings can inform public health surveillance, communication strategies, and digital intervention planning.
- The model effectively captures nuanced risk dimensions within online health discourse.
Related Concept Videos
01:12Relative Risk
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
01:25Models of Health Promotion and Illness Prevention I
A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
02:16Stereotype Content Model
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence categorization, a person will feel...
01:26Modeling in Therapy
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...