Tweets Under the Rubble: Detection of Messages Calling for Help in Earthquake Disaster
This provides situational awareness for rescue and donation efforts in disaster response, but it is incremental as it applies existing methods to a new dataset.
The paper tackles the problem of detecting tweets calling for help during earthquakes, such as the 2023 Turkey and Syria disaster, by developing an interactive tool that classifies tweets and extracts entities with F1 scores up to 98.30 and 84.32, respectively.
The importance of social media is again exposed in the recent tragedy of the 2023 Turkey and Syria earthquake. Many victims who were trapped under the rubble called for help by posting messages in Twitter. We present an interactive tool to provide situational awareness for missing and trapped people, and disaster relief for rescue and donation efforts. The system (i) collects tweets, (ii) classifies the ones calling for help, (iii) extracts important entity tags, and (iv) visualizes them in an interactive map screen. Our initial experiments show that the performance in terms of the F1 score is up to 98.30 for tweet classification, and 84.32 for entity extraction. The demonstration, dataset, and other related files can be accessed at https://github.com/avaapm/deprem