Summary of Enhanced Labeling Technique For Reddit Text and Fine-tuned Longformer Models For Classifying Depression Severity in English and Luganda, by Richard Kimera et al.
Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda
by Richard Kimera, Daniela N. Rim, Joseph Kirabira, Ubong Godwin Udomah, Heeyoul Choi
First submitted to arxiv on: 25 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed labeling approach extracts text from Reddit to facilitate early detection of depression severity using the Beck Depression Inventory questionnaire. The research fine-tunes the Longformer model, outperforming baseline models like Naive Bayes, Random Forest, Support Vector Machines, and Gradient Boosting in both English (48%) and Luganda (45%) languages on a custom-made dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Depression is a serious mental health condition that can be hard to treat. Doctors use the Beck Depression Inventory questionnaire to measure how severe it is and choose the right treatment. But some people don’t want to talk about their depression because they’re afraid of being judged. That’s why many turn to social media for help. This study uses text from Reddit to make detecting depression easier. It works by labeling the text and then using a special model called Longformer. The results show that this model does better than other models like Naive Bayes, Random Forest, Support Vector Machines, and Gradient Boosting in both English and Luganda languages. |
Keywords
* Artificial intelligence * Boosting * Naive bayes * Random forest
