| tags: [text-classification, emotion-detection, roberta, llm-augmentation, hci] | |
| datasets: [dair-ai/emotion] | |
| # MoodShift — RoBERTa+ESA+TF-IDF+FL (Balanced 4500/class) | |
| Novel contribution: LLM-based minority class augmentation via Groq (llama-3.3-70b) | |
| with self-consistency filtering using the trained model itself. | |
| ## Results | |
| | Model | Accuracy | Macro F1 | | |
| |-------|----------|----------| | |
| | Original (imbalanced) | 0.9250 | 0.8849 | | |
| | **LLM-Augmented (4500/class)** | **0.9285** | **0.8893** | | |
| ## Key Improvements | |
| - Love F1: 0.8344 → 0.8613 (+0.0269) | |
| - Surprise F1: 0.7521 → 0.7576 (+0.0054) | |
| ICCA 2026 HCI Research — MoodShift Adaptive Chatbot | |