Indonesian Student Bullying Dataset with 500+ Synthetic Records

500+ pre-split synthetic records analyze school bullying behaviors in Indonesia. The dataset is described as ML-ready, suggesting it is formatted for machine learning tasks. Its origin and specific creation date are unknown.

Use Cases

• Train classification models to identify bullying behaviors based on described behavioral variables.
• Benchmark synthetic data generation techniques for sensitive social topics.
• Analyze patterns in school bullying scenarios within the Indonesian context mentioned in the description.

Strengths

• Contains over 500 records, providing a base volume for analysis.
• Data is pre-split, which may reduce preprocessing effort for model training.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection.

Provenance

Collection Method

Synthetic generation, as indicated by the description.

Geography

Indonesia