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Early Event Detection from Twitter Floods

This project tackles the challenge of real-time event detection using only Twitter data. By leveraging the power of Natural Language Processing (NLP), data mining techniques, and machine learning algorithms, we enable the identification of ongoing events or disasters in specific locations or countries (as long as the NLP adjusted to).

Key features:

  • Live information: Get immediate updates on the most prevalent events, covering areas like earthquakes, floods, terror attacks, traffic jams, and more.
  • Targeted focus: Narrow down your attention to specific locations or countries, ensuring relevant information reaches you quickly.
  • Robust approach: Utilize NLP and data mining techniques to extract meaningful insights from vast amounts of Twitter data.
  • Machine learning power: Harness the predictive capabilities of machine learning algorithms to anticipate and detect emerging events.

Published research:

Our work has been published in the prestigious ACM Digital Library: https://dl.acm.org/doi/10.1145/3110025.3120986

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