Naturkatastrophen Analyse mittels Deep Learning

The study investigates how deep‑learning techniques can automatically classify social‑media texts about natural disasters, using the HUMAID tweet dataset. LSTM, BERT and logistic‑regression models were trained and compared with respect to accuracy, hyper‑parameter effects, and computational cost, revealing that the fine‑tuned BERT model achieves the highest precision while requiring greater processing time. The results demonstrate the potential of advanced NLP models to support rapid, reliable information extraction for emergency response and disaster management.