Summary of Detecting Mental Disorder on Social Media: a Chatgpt-augmented Explainable Approach, by Loris Belcastro et al.
Detecting mental disorder on social media: a ChatGPT-augmented explainable approach
by Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Social and Information Networks (cs.SI)
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 methodology combines Large Language Models (LLMs) with eXplainable Artificial Intelligence (XAI) and conversational agents like ChatGPT to develop an interpretable depression detection model. The novel self-explanatory model, BERT-XDD, uses masked attention to provide both classification and explanations. This approach integrates BERTweet, a Twitter-specific variant of BERT, and enhances interpretability by transforming technical explanations into human-readable commentaries using ChatGPT. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps detect depressive symptoms on social media by creating a model that explains its decisions. It uses special AI models and chatbots to understand why it’s making certain predictions. This is important because many people don’t know how to recognize when someone might be struggling with depression online. The goal is to develop better digital platforms that can help people get support earlier. |
Keywords
* Artificial intelligence * Attention * Bert * Classification
