Datasets:

Fixaro
/

burmese-aspect-based-sentiment

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:

stage1 (stage1_aspect_classification.csv): Multi-label aspect detection dataset containing 6 business aspects and an "All-Zero" baseline class (7,508 rows).
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

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])