BADD: A Large-Scale Bengali Dataset for Arrogance Detection

Arrogant comments are further categorized into five types: Superiority & Self-Importance, Knowledge & Moral Superiority, Contempt & Condescension, Dominance & Entitlement, and Mixed / Other Arrogance. The dataset includes four source/provenance categories: YouTube, Facebook, News portal, and AI. Here, “AI” denotes a data-source category only and does not indicate AI-based annotation.

The canonical Bengali dataset is provided in `BADD_final_dataset_bengali.csv`. Reproducible splits are available as `BADD_train_bengali.csv` (17,941), `BADD_validation_bengali.csv` (2,243), and `BADD_test_bengali.csv` (2,243). An English machine-translated companion is provided in `BADD_final_dataset_english.csv`, and an aligned Bengali-English version in `BADD_final_dataset_bilingual.csv`.

Translation was performed using `facebook/nllb-200-distilled-600M` from `ben_Beng` to `eng_Latn` with deterministic beam search (`num_beams=2`, `do_sample=False`). Only comment text is translated; source, label, and category remain unchanged. Column definitions are provided in `DATA_DICTIONARY.csv`.

Translation settings are recorded in `TRANSLATION_METADATA.json`, while `TRANSLATION_QA_SUMMARY.md` summarizes quality screening. The current QA procedure flags 197 rows for manual inspection; these are screening indicators, not confirmed translation errors. `README.md` provides the package overview and dataset statistics, while `SHA256SUMS.txt` supports file-integrity verification. The Bengali and English files use `comment`, `source`, `arrogance_label`, and `category`; the bilingual file uses `comment_bn`, `comment_en`, `source`, `arrogance_label`, and `category`.

The Bengali dataset is the canonical research version, while the English dataset is a machine-translated companion. BADD supports research in Bangla NLP, text classification, computational social science, toxicity-aware language analysis, and arrogance detection.