Detecting mental disorder on social media: a ChatGPT-augmented explainable approach

• URL: http://arxiv.org/abs/2401.17477v1
• Date: Tue, 30 Jan 2024 22:22:55 GMT
• Title: Detecting mental disorder on social media: a ChatGPT-augmented explainable approach
• Authors: Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio
• Abstract summary: In the digital era, the prevalence of depressive symptoms expressed on social media has raised serious concerns. This paper proposes a novel methodology that effectively combines Large Language Models (LLMs) with eXplainable Artificial Intelligence (XAI) and conversational agents like ChatGPT. explanations are achieved by integrating BERTweet, a Twitter-specific variant of BERT, into a novel self-explanatory model, namely BERT-XDD. The interpretability is further enhanced using ChatGPT to transform technical explanations into human-readable commentaries.
• Score: 1.7999333451993955
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the digital era, the prevalence of depressive symptoms expressed on social media has raised serious concerns, necessitating advanced methodologies for timely detection. This paper addresses the challenge of interpretable depression detection by proposing a novel methodology that effectively combines Large Language Models (LLMs) with eXplainable Artificial Intelligence (XAI) and conversational agents like ChatGPT. In our methodology, explanations are achieved by integrating BERTweet, a Twitter-specific variant of BERT, into a novel self-explanatory model, namely BERT-XDD, capable of providing both classification and explanations via masked attention. The interpretability is further enhanced using ChatGPT to transform technical explanations into human-readable commentaries. By introducing an effective and modular approach for interpretable depression detection, our methodology can contribute to the development of socially responsible digital platforms, fostering early intervention and support for mental health challenges under the guidance of qualified healthcare professionals.

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