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disaster-tweets

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IDRISI is the largest-scale publicly-available Twitter Location Mention Prediction (LMP) datasets, in both English and Arabic languages. It contains 41 disaster events of different types (e.g., floods, fires). Annotations include tagged LMs in posts, location types (e.g., cities, streets), links to OSM toponyms, & usefulness of features for LMD.

  • Updated Jan 23, 2024
  • Jupyter Notebook

🚀 Welcome to my Kaggle submission for "Natural Language Processing with Disaster Tweets." In this challenge, we explore tweets, using NLP to distinguish between those about real disasters and those that aren't. The goal is to build a robust model for accurate disaster-related tweet prediction. 🏆 Impressive F1 score of 0.79926 on the public leader

  • Updated Nov 29, 2023
  • Jupyter Notebook

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