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Workout Application Review Data
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset contains Google Store reviews for a popular Home Workout application. It offers insights into user perceptions of an app designed for daily workout routines, enabling muscle building and fitness at home without needing gym equipment or a coach. The reviews provide a valuable resource for understanding public feedback over time.
Columns
- index: A sequential index for each record.
- review_id: A unique identifier for each review.
- pseudo_author_id: A pseudonymised identifier for the author of the review.
- author_name: The name of the author who submitted the review.
- review_text: The actual text content of the user review.
- review_rating: The numerical rating given by the user, on a scale from 0 to 5. Note that some very early reviews might have a score of 0.
- review_likes: The number of likes or upvotes the review received.
- author_app_version: The version of the application that the author was using when the review was made.
- review_timestamp: The date and time (in UTC) when the review was submitted.
Distribution
This dataset is typically supplied in CSV format, with sample files updated separately to the platform. It comprises approximately 360,000 unique reviews. The dataset's quality is rated highly (5 out of 5) on its listing platform.
Usage
This dataset is ideal for:
- Extracting user sentiments and identifying popular trends.
- Pinpointing which application versions garnered the most positive or challenging feedback.
- Applying topic modelling techniques to uncover common user pain points within the application.
- General market research and app performance analysis.
Coverage
The dataset's coverage is global, encompassing reviews from users worldwide. The time range for the reviews spans from 9th November 2017 to 18th November 2023, providing a multi-year perspective on user feedback.
License
CC0
Who Can Use It
- Data Analysts: To perform sentiment analysis, trend identification, and performance metrics.
- Product Managers: To understand user satisfaction, identify areas for improvement, and inform future development decisions.
- Marketing Specialists: To gauge public perception, identify positive talking points, and refine marketing strategies.
- App Developers: To gain direct feedback on specific versions, features, and overall user experience.
- Researchers: For academic studies on user reviews, mobile application success factors, or natural language processing tasks.
Dataset Name Suggestions
- Home Workout App Google Reviews
- Fitness App User Ratings
- Mobile Exercise App Feedback
- Google Play Home Workout App Reviews
- Workout Application Review Data
Attributes
Original Data Source: 360K HomeWorkout App Google Store Reviews
QUALITY