This repository contains the data of the paper "ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction".
ASAP is a large-scale Chinese restaurant review dataset for Aspect category Sentiment Analysis (ACSA) and review rating Prediction (RP).
ASAP includes 47, 300 genuine user reviews from the Dianping App, a leading Online-to-Offline (O2O) e-commerce platform. Besides a 5-star scale rating, each review is manually annotated according to its sentiment polarities towards 18 pre-defined aspect categories, including food, service, enrionment and so on. We split the dataset into a training set (37,300), a validation set (5,000) and a test set (5,000) randomly.
We hope the release of the dataset could shed some light on the fields of sentiment analysis.
import pandas as pd
data = pd.read_csv(file_path, header=0)
The sentiment polarity over the aspect category is labeled as 1(Positive), 0(Neutral), −1(Negative), −2(Not-Mentioned)
The star rating ranges from 1 to 5.