Datasets:

unicorn-s
/

nepal-border-sentiment-dataset

license: mit
language:
  - ne
  - en
tags:
  - sentiment-analysis
  - nepali
  - low-resource-nlp
  - political-sentiment
task_categories:
  - text-classification
pretty_name: Nepal Border Sentiment Dataset
size_categories:
  - 1K<n<10K

Nepal Border Sentiment Dataset

YouTube comments scraped from 17 Nepali news and commentary channels covering the 2026 Nepal–India border dispute, including the Prime Minister's parliamentary remarks. The dataset is labeled for 3-class sentiment (positive / neutral / negative).

Files

nepal_border_comments.csv — Raw scraped comments with channel and video URL
nepal_comments_labelled.csv — Translated and auto-labeled (silver standard) using cardiffnlp/twitter-xlm-roberta-base-sentiment
comments_manual_review.csv — 300 manually verified samples (gold standard, 100 per class)

Statistics

~2100 unique comments (after deduplication)
Languages: Nepali (Devanagari), Romanized Nepali, English, code-switched
300 manually verified gold-standard labels
~1800 silver-standard (auto-labeled) samples

How it was built

Scraped via youtube-comment-downloader (no API key required)
Translated to English using Google Translate via deep-translator
Auto-labeled with multilingual XLM-RoBERTa sentiment model
300 samples manually verified for the gold-standard split

Limitations

Single annotator for gold-standard labels (no inter-annotator agreement score)
Translation quality varies for Nepali slang and idioms
Class imbalance in auto-labels skewed toward negative sentiment
Sample focused on a specific political event — may not generalize broadly

Use & Citation

Published as a baseline for low-resource Nepali political sentiment NLP. Contributions welcome — see the GitHub repo for the full pipeline.