| --- |
| 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 |
|
|
| ```python |
| 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") |
| ``` |
|
|
