| --- |
| language: |
| - my |
| license: mit |
| tags: |
| - aspect-based-sentiment-analysis |
| - absa |
| - burmese |
| - myanmar |
| - text-classification |
| task_categories: |
| - text-classification |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: stage1 |
| data_files: |
| - split: train |
| path: stage1_aspect_classification.csv |
| default: true |
| - config_name: stage2 |
| data_files: |
| - split: train |
| path: stage2_sentiment_pairs.csv |
| --- |
| |
| # Burmese Aspect-Based Sentiment Analysis (ABSA) Dataset |
|
|
| This dataset contains Burmese customer reviews annotated for two-stage Aspect-Based Sentiment Analysis (ABSA). |
|
|
| ## Dataset Subsets (Configurations) |
|
|
| This repository contains two subsets: |
|
|
| 1. **`stage1` (`stage1_aspect_classification.csv`)**: Multi-label aspect detection dataset containing 6 business aspects and an "All-Zero" baseline class (7,508 rows). |
| 2. **`stage2` (`stage2_sentiment_pairs.csv`)**: Aspect-level sentiment classification pairs (Positive, Negative, Neutral). |
|
|
| --- |
|
|
| ## Aspect Definitions (Stage 1) |
| - `product_or_service_quality`: Product durability, food taste, design, cleanliness. |
| - `fulfillment_and_speed`: Delivery time, packaging, shipping speed. |
| - `price_and_value`: Value for money, discounts, price fairness. |
| - `digital_experience`: App/website usability, UI/UX, online payment systems. |
| - `customer_support`: Staff friendliness, responsiveness, helpline support. |
| - `variety_and_availability`: Stock availability, color/size options, menu choices. |
|
|
| ## Sentiment Classes (Stage 2) |
| - `Positive` |
| - `Negative` |
| - `Neutral` |
|
|
| --- |
|
|
| ## How to Load in Python |
|
|
| ```python |
| from datasets import load_dataset |
| |
| REPO_ID = "Fixaro/burmese-aspect-based-sentiment" |
| |
| # 1. Load Stage 1 (Aspect Detection) |
| dataset_stage1 = load_dataset(REPO_ID, "stage1") |
| print("Stage 1 Sample:", dataset_stage1['train'][0]) |
| |
| # 2. Load Stage 2 (Aspect Sentiment Analysis) |
| dataset_stage2 = load_dataset(REPO_ID, "stage2") |
| print("Stage 2 Sample:", dataset_stage2['train'][0]) |
