Datasets:
metadata
language:
- ro
- it
license: cc-by-4.0
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: RoIt-XMASA
size_categories:
- 100K<n<1M
tags:
- sentiment-analysis
- cross-lingual
- cross-domain
- romanian
- italian
- reviews
RoIt-XMASA
Romanian–Italian Cross-domain Multi-domain Sentiment Analysis
RoIt-XMASA is a multilingual, cross-domain sentiment analysis dataset containing user reviews in Romanian (RO) and Italian (IT) across three domains: Books, Movies, and Music. Reviews are annotated with 1–5 star ratings (excluding 3).
Dataset Summary
| Split | Rows | Labeled |
|---|---|---|
| train | 12,000 | yes |
| validation | 12,000 | yes |
| test | 12,000 | yes |
| unlabeled | 202,141 | no |
Splits breakdown (labeled)
Each labeled split is perfectly balanced:
- Domains: 4,000 reviews per domain (Books / Movies / Music)
- Languages: 6,000 reviews per language (RO / IT)
Data Fields
| Field | Type | Description |
|---|---|---|
id |
int64 | Unique review identifier |
title |
string | Review title (may be empty) |
text |
string | Review body |
domain |
string | Domain: Books, Movies, or Music |
language |
string | Language code: RO (Romanian) or IT (Italian) |
rating |
int64 | Star rating: 1, 2, 4, or 5 (null for unlabeled) |
Usage
from datasets import load_dataset
ds = load_dataset("avramandrei/RoIt-XMASA")
# Labeled splits
train = ds["train"]
val = ds["validation"]
test = ds["test"]
# Filter by language or domain
ro_books = train.filter(lambda x: x["language"] == "RO" and x["domain"] == "Books")