Research Paper Accepted at ICEFronT 2026
Contributed to a research paper on MentalBERT-based depression-related text classification accepted at ICEFronT 2026 under Paper ID 792.
A research paper I contributed to, “MentalBERT Based Depression Detection from Social Media: Comparing Classical, Hybrid and Transformer Models,” was accepted at ICEFronT 2026 under Paper ID 792.
The study compares classical machine learning, hybrid approaches, and transformer models using Twitter and Reddit posts. It examines how these approaches perform on depression-related text classification, with fine-tuned MentalBERT reporting the strongest performance among the evaluated models.
This acceptance marks a milestone in my academic research journey and reflects my involvement in work that combines natural language processing, model comparison, and mental health-related text analysis.