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dat201204/vietnamese-caucu-comments

Vietnamese Cau Cuu Facebook Comments Dataset Summary This dataset contains Vietnamese Facebook comments collected from a natural-disaster discussion thread and auto-labeled for binary emergency detection. The target task is to detect whether a comment is a real-time rescue request (cau_cuu) versus a non-emergency comment (khong_phai_cau_cuu). This release is intended as a bootstrap dataset for triage modeling and should be treated as a weakly supervised resource.… See the full description on the dataset page: https://huggingface.co/datasets/dat201204/vietnamese-caucu-comments.

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Dataset Card

Vietnamese Cau Cuu Facebook Comments

Dataset Summary

This dataset contains Vietnamese Facebook comments collected from a natural-disaster discussion thread and auto-labeled for binary emergency detection.

The target task is to detect whether a comment is a real-time rescue request (cau_cuu) versus a non-emergency comment (khong_phai_cau_cuu).

This release is intended as a bootstrap dataset for triage modeling and should be treated as a weakly supervised resource. Human review is strongly recommended before production use.

Task Definition

  • 0: khong_phai_cau_cuu Non-emergency content such as sympathy, reposts, hotline aggregation, updates that the family is already safe, or unrelated discussion.
  • 1: cau_cuu Active rescue requests where people are trapped, in immediate danger, isolated, or explicitly requesting emergency evacuation/support.

Priority metric for downstream models: recall on label 1.

Data Source

  • Source type: Vietnamese Facebook comments from a disaster-related post/thread.
  • Data was flattened from both top-level comments and nested replies.
  • Original extraction and weak labeling were produced locally for research and experimentation.

Data Fields

  • id: Stable synthetic identifier derived from comment tree position.
  • text: Raw Vietnamese comment text.
  • label: Binary weak label (0 or 1).
  • confidence: Heuristic confidence score from the auto-labeling pipeline.

Class Distribution

Current version statistics:

  • Total rows: 1492
  • Label 0: 1050
  • Label 1: 442

Labeling Method

Labels were assigned with a rule-based weak supervision pipeline using:

  • urgent rescue keywords such as cứu, mắc kẹt, ngập tới mái, khẩn cấp, SOS
  • structural signals such as phone numbers, map links, GPS-like coordinates, and location mentions
  • negative filters for resolved cases (đã được cứu, đã an toàn) and hotline/broadcast style comments

Because labels are weakly supervised, false positives and false negatives remain possible.

Recommended Use

  • Training or bootstrapping a Vietnamese emergency comment classifier
  • Error analysis and heuristic refinement
  • Human-in-the-loop triage experiments

Limitations and Ethics

  • Comments may contain sensitive situational information such as phone numbers and addresses.
  • Labels are machine-generated and not fully human-verified.
  • Do not use this dataset for surveillance or any harmful downstream purpose.
  • Review privacy, legal, and platform-policy constraints before redistribution or deployment.

Citation

If you use this dataset, please cite the project/repository that publishes this dataset card and describe it as a weakly supervised Vietnamese rescue-request classification dataset.