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Tweets Under the Rubble: Detection of Messages Calling for Help in Earthquake Disaster

arXiv 2302.13403 ↗First posted 26 Feb 2023cs.SI cs.CL cs.IRcited by 0

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Abstract (arXiv)

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

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 30 references that are in the map. First posted on arXiv 26 Feb 2023.

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11 of 30 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
  3. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,219
  4. 2018CrisisMMD: Multimodal Twitter Datasets from Natural Disasterscited by 88
  5. 2020ConvBERT: Improving BERT with Span-based Dynamic Convolutioncited by 88
  6. 2016Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messagescited by 43
  7. 2021HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarkscited by 38
  8. 2018Domain Adaptation with Adversarial Training and Graph Embeddingscited by 30
  9. 2020Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Responsecited by 19
  10. 2018A Twitter Tale of Three Hurricanes: Harvey, Irma, and Mariacited by 12
  11. 2016Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networkscited by 4

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