Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer
  Models for Classifying Depression Severity in English and Luganda
Richard Kimera Daniela N. Rim Joseph Kirabira Ubong Godwin Udomah Heeyoul Choi
Depression is a global burden and one of the most challenging mental health
conditions to control. Experts can detect its severity early using the Beck
Depression Inventory (BDI) questionnaire, administer appropriate medication to
patients, and impede its progression. Due to the fear of potential
stigmatization, many patients turn to social media platforms like Reddit for
advice and assistance at various stages of their journey. This research
extracts text from Reddit to facilitate the diagnostic process. It employs a
proposed labeling approach to categorize the text and subsequently fine-tunes
the Longformer model. The model's performance is compared against baseline
models, including Naive Bayes, Random Forest, Support Vector Machines, and
Gradient Boosting. Our findings reveal that the Longformer model outperforms
the baseline models in both English (48%) and Luganda (45%) languages on a
custom-made dataset.