Depression detection in social media posts using transformer-based models and auxiliary features
Bibliographic Data
| ID | 16858758 |
|---|---|
| Authors | Marios Kerasiotis (National Technical University of Athens), Loukas Ilias (0000-0002-4483-4264, National Technical University of Athens, corresponding author), Dimitris Askounis (0000-0002-2618-5715, National Technical University of Athens) |
| Year | 2024 |
| Volume | 14 |
| Issue | 1 |
| Publication date | 2024-09-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-024-01360-4 |
| OpenAlex | W4402938061 |
| Language | EN |
| Citations received | 4 |
| References cited | 51 |
Electrical engineering · Social media · Transformer · Voltage · World Wide Web · Computer Science · Engineering · Mental Health via Writing · Sentiment Analysis and Opinion Mining · Spam and Phishing Detection · Artificial Intelligence
Transformers
Facebook language predicts depression in medical records
Multitask learning for recognizing stress and depression in social media
A Multimodal Framework for Depression Detection During Covid-19 via Harvesting Social Media
Calibration of Transformer-Based Models for Identifying Stress and Depression in Social Media
Deptweet
Identifying discernible indications of psychological well-being using ML
| Citations per year | 4 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |