Emotion analysis using deep learning is evolving rapidly with advancements in NLP, multimodal learning, and explainable AI. Researchers are exploring various approaches, including transformer-based models, multimodal fusion techniques, real-time emotion recognition, and knowledge graph integration. What are the latest emerging trends, challenges, and potential future directions in this field?
I think currently there are at least 7 trends in emotion research, namely: Multi-Modal Emotion Recognition, Emotion Detection from Text Using Large Language Models (LLMs), Graph Neural Networks (GNN) for Emotion Analysis in Social Media, Emotion Recognition in Real-Time Context and Edge AI, Explainability & Interpretability in Emotion AI, Few-shot & Zero-shot Learning for Emotion Analysis, Emotion Analysis in Metaverse & VR
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