Halodoc and Alodokter Digital Health App User Review Dataset for Sentiment Analysis
Description
This dataset contains user reviews collected from digital health applications available on the Google Play Store. The data were obtained using a web scraping approach during the period of January 2024 to October 2025. The dataset was created to support research in sentiment analysis, text mining, and natural language processing (NLP). The dataset is intended for evaluating and comparing text representation methods, including Term Frequency-Inverse Document Frequency (TF-IDF) and Word2Vec, as well as classification using the Support Vector Machine (SVM) algorithm.
Files
Steps to reproduce
1. Collect user reviews from the Google Play Store using a web scraping technique. 2. Filter reviews related to digital health applications. 3. Remove duplicate and incomplete records. 4. Perform text preprocessing including case folding, cleaning, stop-word removal, and stemming. 5. Label the sentiment data into positive and negative classes. 6. Save the processed dataset in CSV format. Use the dataset for sentiment analysis experiments with TF-IDF, Word2Vec, and Support Vector Machine (SVM).