MOGAM: A Multimodal Object-oriented Graph Attention Model for Depression Detection

arXiv:2403.15485v1 Announce Type: cross
Abstract: Early detection plays a crucial role in the treatment of depression. Therefore, numerous studies have focused on social media platforms, where individuals express their emotions, aiming to achieve early detection of depression. However, the majority of existing approaches often rely on specific features, leading to limited scalability across different types of social media datasets, such as text, images, or videos. To overcome this limitation, we introduce a Multimodal Object-Oriented Graph Attention Model (MOGAM), which can …

abstract arxiv attention cs.ai cs.cl cs.lg depression detection emotions express features graph however media multimodal object object-oriented platforms role social social media social media platforms studies treatment type